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213 commits

Author SHA1 Message Date
Satoshi Misumi
852f92780c
Fix M_PI being unavailable where _USE_MATH_DEFINES comes too late (#4023)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-21 15:45:41 +00:00
GuySten
61c8a59cff
Override NJOY default damage energy threshold (#4022)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-20 14:52:30 +00:00
Mazeyar Moeini Feizabadi
05d01274a7
Add analytic tests for ray-traced intersection distances (#4014)
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2026-07-19 14:49:48 -05:00
Joffrey Dorville
db673b9acb
Automatic C++ doc generation (#3950)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-17 15:47:40 +00:00
GuySten
796ae384b8
Fix not reseting filter_matches corrupt pulse height results (#4019)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-17 13:18:53 +00:00
GuySten
d3bc1669d3
Access element subshell map data only if it has atomic relaxation data (#4020) 2026-07-17 07:40:16 -05:00
Paul Romano
f1fb6721f0
Performance optimizations for shared secondary bank (#4011)
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2026-07-17 01:25:18 +00:00
Ethan Peterson
c55c578812
Native parametric tokamak source (#3999)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-16 09:54:56 -05:00
Paul Romano
16cde42ff4
Enable parent-nuclide tally breakdowns in R2S calculations (#4013)
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Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-07-16 00:00:42 +03:00
Lewis Gross
243c249533
normalize new_u after periodic crossing to prevent unnormalized direction (#4015)
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2026-07-15 08:57:53 -05:00
Eden
e783e01471
Add chain parameter to Material.get_activity for half-life data (#3957)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-11 06:18:26 +00:00
Jonathan Shimwell
7256d5046a
extra checks for pixels (#4009)
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Co-authored-by: Jonathan Shimwell <jon@proximafusion.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-10 15:02:14 +00:00
Paul Romano
216651b69e
Shared secondary bank performance optimizations (#3995) 2026-07-10 09:22:16 -05:00
Paul Romano
7c408f6a10
Replace Ben Forget with John Tramm on technical committee (#4008)
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2026-07-10 09:48:11 +02:00
Paul Romano
3c3ebba98b
Turn on weight windows if weight_windows_file is specified (#4007)
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2026-07-09 23:59:33 +00:00
GuySten
e73d8048da
Support cell densities per instances in plots (#4006)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-09 22:45:09 +00:00
Jonathan Shimwell
5203640549
Further input validation for plot methods (#4004) 2026-07-09 16:55:32 -05:00
Paul Romano
3cdb67e50d
Store slice overlap indices in cell ID field (#4002)
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2026-07-09 11:47:55 +02:00
Paul Romano
8b15ee3915
Add Jon Shimwell to technical committee (#4001)
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2026-07-08 11:25:21 -05:00
Andrew Davis
8684506269
This fixes compile isuees found with GCC 16.1.1 and FMT version (#4000)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-07 14:58:19 +00:00
viktormai
0c6b3fb835
Overlap detection for plotter (#3969)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-06 17:47:22 +00:00
Paul Romano
3fcb9692be
Make sure output is treated consistently in R2SManager (#3994)
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2026-07-04 22:20:03 -05:00
Matteo Zammataro
e3bc615172
Fix numerical cancellation in RectLattice::distance for large pitch values (#3853)
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Co-authored-by: matteo.zammataro <matteo.zammataro@newcleo.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-03 21:39:17 +00:00
Paul Romano
66359e5dd8
Fix surface tally crash on lattice crossings (#3993)
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
2026-07-03 15:52:19 -05:00
Matteo Zammataro
97e04c464a
Add ambient dose coefficients (H*(10)) from ICRP74 (#3256)
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Co-authored-by: matteo.zammataro <matteo.zammataro@newcleo.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-02 23:51:10 +00:00
Jon Shimwell
df6f94300f
Turn the weight window game off for a zero or negative lower bound (#3990)
Co-authored-by: John Tramm <john.tramm@gmail.com>
Co-authored-by: shimwell <mail@jshimwell.com>
2026-07-02 13:04:02 -05:00
Paul Romano
3247587d49
Ensure photon cross sections are loaded when FileSource contains photons (#3988)
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2026-07-02 11:54:12 -05:00
John Tramm
24fdb84edc
Tally 32-bit Overflow Fix (#3960)
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-07-02 11:53:49 -05:00
John Tramm
f01852411d
Random Ray Forward Flux Save in Adjoint Mode (#3962)
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-01 22:35:27 +02:00
Jonathan Shimwell
d06fdee93a
Preserve user material names in convert_to_multigroup and avoid overwriting material with same name bug fix (#3984)
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2026-06-30 09:38:09 -05:00
GuySten
4d6244d93c
Fix for numpy 2.5.0 (#3981)
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2026-06-24 16:09:16 -05:00
Paul Romano
608a1c3386
Fix several issues related to independent operator depletion (#3977)
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2026-06-23 09:00:47 +02:00
stetsonschott
09ee8308d0
Replaced 'C0' by elemental carbon in `openmc/examples.py'. (#3974)
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2026-06-17 20:33:40 -05:00
GuySten
02eb999af1
fix tmate start only on successful tests (#3954)
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2026-06-08 22:09:25 -05:00
Logan Harbour
998565808e
Use non-deprecated methods for getting libMesh node points (#3963) 2026-06-08 22:07:21 -05:00
Patrick Shriwise
ea6ba328c9
Fix collision track feature for photon transport (#3946)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-06-08 23:37:34 +00:00
Paul Romano
4f6a25e00a
Introduce new C API function for slice plots (#3806)
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2026-06-08 21:08:08 +00:00
Paul Romano
db322f2c5d
Add section in depletion user's guide about comparing to other codes (#3955) 2026-06-08 18:22:32 +00:00
EdenRochmanSharabi
111eb77066
Implement SphericalMesh.get_indices_at_coords (#3919)
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Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-30 06:18:09 +00:00
Jonathan Shimwell
219d82726f
Allow tracklength estimator for neutron heating (#3915)
Co-authored-by: Jon Shimwell <jon@proximafusion.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-30 06:10:05 +00:00
hugo-barthod
2dd5322fee
Fix undefined variable in openmc.mgxs.library (scatt_mgxs) (#3943)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-30 05:35:31 +00:00
Bor Kos
46d8896132
Pulsed Height Tally in mixed neutron-gamma fields (#3937)
Co-authored-by: Bor Kos <bor.kos@bakerhughes.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-30 03:25:38 +00:00
Jon Shimwell
ddabe1c8c5
Avoid storing inconsistent sum/sum_sq on summed D1S tallies (#3949)
Co-authored-by: shimwell <mail@jshimwell.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-30 03:25:22 +00:00
Paul Romano
1914e3eefa
Support endf.Material in from_endf methods (#3932) 2026-05-29 21:53:45 -05:00
Ahnaf Tahmid Chowdhury
dfb6c5699c
Modernize CMake packaging (#3653)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-21 20:33:56 +00:00
Patrick Shriwise
7d09a12606
DAGMC Cell Override Updates (#3888)
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-20 21:43:21 +00:00
Patrick Shriwise
66497e76b1
Support writing of hex elements to VTKHDF format. (#3623)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-05-20 14:01:21 -05:00
Hridoy Kabiraj
3c7a030d43
Guard average molar mass and validate materials depletion inputs (#3941) 2026-05-20 13:49:00 -05:00
John Tramm
0169fd9226
Shared Secondary Particle Bank (#3863)
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
Co-authored-by: Copilot <copilot@github.com>
2026-05-19 23:23:10 -05:00
charliesheh
beed56e6ee
Check for missing thread count argument for -s/--threads (#3940) 2026-05-18 13:35:56 -05:00
Hridoy Kabiraj
195dff6d1d
Fix missing volume checks in material activity/decay heat (#3939) 2026-05-18 09:20:59 -05:00
Paul Romano
d56cda2544
Implement DecaySpectrum distribution type and utilize in R2S (#3930)
Co-authored-by: Copilot <copilot@github.com>
2026-05-08 20:53:12 -05:00
Paul Romano
f3e1066d46
Include mass_attenuation.h5 in package data (#3936) 2026-05-07 23:50:23 +00:00
Jonathan Shimwell
e542b2f035
Allow Mesh.volumes property for 1D and 2D RegularMesh (#3914) 2026-05-06 10:07:35 -05:00
Jack Fletcher
368ea069ca
Local adjoint source for Random Ray (#3717) 2026-04-28 16:10:03 -05:00
Paul Romano
1116c4bdc0
Support multiple meshes in R2S calculations (#3860) 2026-04-28 10:02:08 -04:00
Travis L.
806fb4ce77
Clean up MCPL references (#3927) 2026-04-27 09:40:44 -05:00
Perry
2d5c50080c
Allow the use of substeps for CRAM (#3908)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-22 18:24:34 -05:00
Perry
1f7ac4215f
Clip negative atom densities that result from CRAM (#3879)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-21 20:24:53 +00:00
Ethan Peterson
a1df5842e0
Remove self loops from spontaneous fission decay mode (#3907)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-21 16:47:40 +00:00
Lorenzo Chierici
e431d49bec
Add reactivity control to coupled transport-depletion analyses (#2693)
Co-authored-by: Andrew Johnson <drewejohnson@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-20 07:13:53 -05:00
Luke Labrie-Cleary
36e70d8efc
Add Arch Linux User Repository (AUR) installation instructions to documentation (#3921)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-18 16:01:09 +00:00
Paul Romano
fd1bc26af0
Pin NJOY version in Dockerfile (#3920) 2026-04-09 23:13:18 +03:00
Paul Romano
1eb368bbd2
Pin NJOY version in CI to 2016.78 (#3917) 2026-04-09 09:31:27 +02:00
Paul Romano
23e8a11102
Update versions of several GHA Actions (#3913) 2026-04-05 14:04:34 -05:00
Jonathan Shimwell
542f949fa0
Use local variable to avoid attribute lookup in form_rxn_matrix loop (#3884)
Co-authored-by: Perry <yrrepy@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-04 20:53:50 +00:00
GuySten
efc542825e
Add the ability to tally microscopic cross sections in void materials with tracklength estimator (#3771)
Co-authored-by: Jonathan Shimwell <drshimwell@gmail.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-04 20:32:51 +00:00
Ethan Peterson
60d1dfba7f
Refactor form_matrix method on depletion chain class (#3892)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-03 21:27:39 +00:00
John Tramm
b215f13218
RAG search tool for agents (#3861)
Co-authored-by: John Tramm <jtramm@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-03 16:18:19 -05:00
Jonathan Shimwell
9ff50499e1
Adding per m3 to material functions (#3912)
Co-authored-by: Jon Shimwell <jon@proximafusion.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-03 00:00:02 +00:00
bessemoa
df985e10b3
Add from_bounding_box classmethod to structured mesh classes (#3903)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-02 22:51:33 +00:00
Jonathan Shimwell
ca22a5174a
adding pdf to read the docs (#3893) 2026-04-02 17:01:30 -05:00
GuySten
d9b30bbbd5
Approximate multigroup velocity (#3766)
Co-authored-by: Adam Nelson <1037107+nelsonag@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-04-02 16:59:02 +00:00
Md. Ariful Islam
97d9a839c2
Fix MPI depletion hang (#3910) 2026-04-02 11:30:09 -05:00
April Novak
8223099ed9
All reduce to print correct number of surface source particles (#3901) 2026-03-26 12:35:12 -05:00
GuySten
6cd39073b3
Fix surface tally when crossing lattice (#3895) 2026-03-23 10:16:59 -05:00
Paul Romano
3ce6cbfdda
Add fusion_neutron_spectrum to openmc.stats module (#3862) 2026-03-17 22:10:18 +01:00
itay-space
1578698129
Implement angular PDF evaluation for angle-energy distributions (#3550)
Co-authored-by: Your Name <you@example.com>
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
Co-authored-by: Eliezer214 <110336440+Eliezer214@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-14 23:58:17 +02:00
Marco De Pietri
bc9c31e0f9
get indices for rectilinear meshes (#3876)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-14 04:19:51 +00:00
Paul Wilson
dd6d31bfae
Add properties to settings w/ documentation, c++ loading of filename, and python round-trip test (#3808)
Co-authored-by: Patrick C Shriwise <pshriwise@gmail.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-13 21:40:52 +00:00
AlvaroCubi
4bda85f17e
Allow StepResult.get_material to accept integer material ID (#3872)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-12 15:04:42 -05:00
Christopher Ashe
c44d2f0b43
Allow groups to be passed as sequence of floats in convert_to_multigroup (#3873)
Co-authored-by: Jonathan Shimwell <drshimwell@gmail.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-12 19:47:47 +00:00
Paul Romano
27522fe851
Improve review skill instructions for determining PR context (#3875) 2026-03-12 14:27:00 -05:00
CoronelBuendia
387b41ab65
Change plotting docstring to specify integer RGB values (#3868) 2026-03-12 12:35:10 -05:00
Eshed Magali
ba94c58230
Closing the stdout file descriptor when finished (#3864) 2026-03-11 16:50:58 +00:00
Amanda Lund
1dc4aa9882
Add setting to optionally disable atomic relaxation (#3855)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-10 04:00:10 +00:00
Paul Romano
908e63115a
Add reusable reviewing-openmc-code skill and Copilot Review agent (#3842)
Co-authored-by: John Tramm <john.tramm@gmail.com>
2026-03-05 21:40:36 -06:00
GuySten
be4148ad0d
Refactor Ray class into its own file (#3845)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-06 01:07:42 +00:00
Paul Romano
6f72619729
Fix include guard in output.h (#3856) 2026-03-05 23:29:36 +00:00
John Tramm
533f09defd
Enable CMake "compile_commands.json" Output (#3854)
Co-authored-by: John Tramm <jtramm@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-05 23:20:54 +00:00
Paul Romano
dbfd6387b2
Fix two docstrings that should have r prefix (#3851) 2026-03-05 07:37:47 +02:00
Ethan Peterson
2bd06660c5
Parallelize sampling external sources and threadsafe rejection counters (#3830)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-04 14:36:43 -06:00
GuySten
0ab46dfa35
Fix cell data parsing (#3848) 2026-03-04 06:56:49 -06:00
GuySten
70be650003
Implement surface flux tallies (#3742)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-04 14:17:48 +02:00
Patrick Shriwise
b796afb591
Correction to surface normal determination in SolidRayTrace plots (#3846) 2026-03-04 14:10:54 +02:00
Marco De Pietri
53d98ce71a
Add method on Material for computing photon contact dose rate (#3700)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-03-03 15:48:56 +00:00
Paul Romano
49b896b0eb
Enable "hybrid" tallies in get_microxs_and_flux (#3831) 2026-03-02 22:06:52 -05:00
GuySten
823b4c96c9
Speed up depletion with transfer rates (#3839) 2026-03-02 06:53:20 -06:00
Paul Romano
83a7b36add
Speed up Docker build (#3841)
Co-authored-by: Jonathan Shimwell <drshimwell@gmail.com>
2026-03-01 21:52:51 +02:00
Paul Romano
b3788f11e1
Use clang-format version 18 for CI format checks (#3840) 2026-02-27 13:56:00 +02:00
Micah Gale
1d9a8f542b
Add Python 3.14 to testing matrix and drop Python 3.11 (#3642)
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-26 18:18:04 -06:00
Paul Romano
3b5ac08bfb
Skip DAGMC lost particles test (#3836) 2026-02-26 11:26:39 -06:00
Paul Romano
17d4164242
Update copyright to 2026 (#3834) 2026-02-26 08:14:28 +00:00
GuySten
322b741fde
Support Mixture distributions in combine_distributions (#3784)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-26 07:30:08 +00:00
Jonathan Shimwell
6050c789ca
making use of endf.get_evaluations (#3819)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-26 03:14:44 +00:00
GuySten
3ba8a9f078
Correctly score pulse height tally when no cell filter is present (#3821)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-26 02:44:17 +00:00
Jonathan Shimwell
8081815b99
Add RegularMesh.get_indices_at_coords method (#3824)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-26 02:19:02 +00:00
John Tramm
54c8e3d6eb
Speedup CI and Improve Reproducibility Across Compilers (#3823)
Co-authored-by: John Tramm <jtramm@gmail.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-25 17:12:18 -06:00
GuySten
2a38dc11ec
Do not fail CI when coveralls.io is not available. (#3835) 2026-02-25 15:04:00 -06:00
GuySten
c0427dd40a
Resolve conflict with weight windows and global russian roulette (#3751)
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
2026-02-25 14:01:33 -06:00
Patrick Shriwise
5a85bd92f2
C++ formatting suggestions on PRs (#3829) 2026-02-25 11:08:04 -06:00
Jonathan Shimwell
3ff6b59a49
Allow Mesh.from_domain to use bounding boxes directly (#3828) 2026-02-24 23:44:30 -06:00
Paul Romano
e130701f10
Fix MeshFilter.get_pandas_dataframe to handle all mesh types (#3817) 2026-02-24 07:35:23 +00:00
Vitaly Mogulian
8c24c1c064
Modify the plotter ray tracing for its utilization in estimators (#3816)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-24 06:46:21 +00:00
GuySten
83a30f6860
Support arbitrary symmetry axis for CylindricalIndependent class (#3474)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-21 20:00:36 +00:00
Paul Romano
139907c955
Implement tally filter for filtering by reaction (#3809) 2026-02-21 10:17:12 -06:00
Jonathan Shimwell
153281a490
Remove unused class Tabulated2D (#3818) 2026-02-21 15:00:22 +00:00
John Tramm
53ce1910f9
Fix S2 Random Ray Casting Issue (#3825) 2026-02-19 18:25:31 +00:00
Kevin Sawatzky
efefdb17b1
Add more operator overloads in the new Tensor class (#3822) 2026-02-19 11:03:19 -06:00
Kevin Sawatzky
417343c920
Implement S2 directional sampling in the random ray solver (#3811) 2026-02-19 14:25:19 +02:00
GuySten
f007c85a50
Check for positive radii (#3813) 2026-02-19 08:36:12 +00:00
Jonathan Shimwell
6d6b051507
avoid need to set particles and batches for dagmc models when calling convert_to_multigroup (#3801)
Co-authored-by: Jon Shimwell <jon@proximafusion.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-02-18 11:18:05 -06:00
GuySten
d4dc089618
Remove redundant check (#3812) 2026-02-18 09:09:39 -06:00
John Tramm
977ade79a1
Replace xtensor with internal Tensor/View classes (#3805)
Co-authored-by: John Tramm <jtramm@gmail.com>
2026-02-17 09:50:38 -06:00
Kevin Sawatzky
c6ef84d1d5
Set upper and lower interpolation bounds for MGXS data. (#3803) 2026-02-15 23:59:08 +02:00
Paul Romano
a35927aad3
Extend ParticleProductionFilter to support multiple particle types (#3780) 2026-02-13 22:18:29 -06:00
GuySten
7fc5b94877
Store atomic mass in ParticleType. (#3765)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-14 03:14:03 +00:00
Kevin Sawatzky
19c0aafdc6
Fix None values appearing in cross section data generated with Model.autoconvert (#3802) 2026-02-13 18:52:10 +02:00
Patrick Shriwise
bcb9395207
SolidRayTracePlot CAPI (#3789)
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-02-13 07:54:27 +02:00
GuySten
b145fdd999
Improve radial crossing checks in SphericalMesh and CylindricalMesh (#3792)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-13 05:10:20 +00:00
Jonathan Shimwell
4e5deed0cc
Using ``_LIBRARY` and `_SUBLIBRARY`` from endf package (#3804) 2026-02-13 03:25:49 +00:00
Paul Romano
8198e6021d
Add truncated normal distribution support (#3761) 2026-02-12 18:25:56 +02:00
Patrick Shriwise
a3426cf833
Fix weight windows regression test (#3798) 2026-02-12 06:30:31 -06:00
Jonathan Shimwell
8d0fe6c71d
making use of sum_rules in endf package (#3799) 2026-02-12 10:11:28 +00:00
Jonathan Shimwell
26b13083f3
Use gnds_name and zam from endf package (#3796) 2026-02-12 05:58:00 +00:00
GuySten
96383fcb2b
More interpolation types in Tabular. (#3413)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-11 21:05:07 +00:00
azim-givron
360ec24b41
Implement vector fitting to replace external vectfit package (#3493)
Co-authored-by: azim_givron <a.givron@naarea.fr>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-02-11 10:00:18 -06:00
Matthew Feickert
44da7022b8
FIX: Remove setuptools from run dependencies (#3794) 2026-02-11 09:21:13 -06:00
Jonathan Shimwell
3f20a5e228
Use several data variables from endf package (#3787) 2026-02-10 06:41:04 -06:00
Jonathan Shimwell
8053111f2d
making use of endf-python package more (#3786)
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
2026-02-10 02:08:25 +00:00
Kevin Sawatzky
4f4930b633
Temperature feedback support in the random ray solver. (#3737) 2026-02-09 16:54:59 -06:00
Paul Romano
d0346e94ac
Install parallel h5py with no build isolation (#3782) 2026-02-08 22:22:39 +00:00
Patrick Shriwise
6efc9db7b3
Modifications to C++ plots for interactive raytrace plots (#3776) 2026-02-08 12:11:19 -06:00
GuySten
04bee9c49f
Check that Surface IDs are at least 1 (#3772)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-06 18:44:16 +00:00
Lewis Gross
a632429267
Move distrib (mat, temp, dens) from XML attribute to subelement for better compatibility with very large instance lists (#3774) 2026-02-06 19:32:32 +02:00
Kevin Sawatzky
14acc762bc
C-API bindings for key random ray functions (#3749) 2026-02-06 10:42:32 -06:00
Jonathan Shimwell
8a62a97115
openmc.Tally creation from constructor (#3777) 2026-02-06 10:23:11 -06:00
Jonathan Shimwell
6f625f3dea
Precompute offsets in random ray source update (#3775) 2026-02-06 09:25:14 -06:00
Gavin Ridley
f2c936cf5b
Implement filter for secondary particle production binned by energy (#3453)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-02-05 18:00:03 -06:00
Jonathan Shimwell
1039b5d9ff
Parallelize transpose of scattering matrix for random ray adjoints (#3768) 2026-02-05 10:43:16 -06:00
Paul Romano
3b619d6904
Fix use of length multiplier in several LibMesh methods (#3773) 2026-02-04 22:29:30 -06:00
David Andrs
a22238e069
Fixing compiler warning about VLA (Clang extension) (#3769) 2026-02-04 14:50:38 -06:00
Paul Romano
b41e22f68b
Refactor ParticleType to use PDG Monte Carlo numbering scheme (#3756)
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
Co-authored-by: Amanda Lund <alund1187@gmail.com>
2026-02-03 07:23:24 +00:00
Ethan Peterson
fc0d9eec65
Ignore all source build directories that match build* pattern (#3762) 2026-02-02 09:55:45 -06:00
David Andrs
6041ee6ae3
SpatialBox can be constructed via ctor with parameters (#3760) 2026-01-31 17:02:39 -06:00
GuySten
7b4617affb
Fix for plotting model with multi-group cross sections (#3748)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-30 06:10:16 +00:00
Paul Romano
f7a734189a
Optionally compute bounding boxes in Mesh.material_volumes (#3731) 2026-01-29 09:20:48 +02:00
GuySten
008d584607
Warn users when setting undefined attributes in ``openmc.Settings`` (#3746)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-28 08:02:02 +00:00
Jonathan Shimwell
db426b66ca
Materials name persist when running depletion simulation (#3738)
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-27 06:06:36 +00:00
Paul Romano
5c502ddb3e
Do not add radioactive Ta180 when calling add_element('Ta') (#3750) 2026-01-26 19:09:58 +02:00
Kevin Sawatzky
3e2f1f521a
Enable fission heating tallies in the random ray solver (#3714) 2026-01-23 10:23:05 -06:00
Olek
73a98b2cc6
Add random_ray_pincell() example model (#3735)
Co-authored-by: John Tramm <john.tramm@gmail.com>
2026-01-23 10:20:25 -06:00
Olek
049a852e52
Random Ray main function and autosetup refactoring (#3733) 2026-01-22 15:21:47 -06:00
GuySten
6b43a298f4
Add n_elements to the MeshBase protocol and deprecate num_mesh_cells (#3745) 2026-01-22 15:04:30 +00:00
GuySten
c5df2bf621
Fix for pandas version 3 (#3743) 2026-01-21 21:57:40 -06:00
GuySten
2691ff8a0f
Fix type hinting and simplify implementation of combine_distributions (#3445)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-21 14:33:30 +00:00
Kevin Sawatzky
5847b0de23
Block restriction of libMesh unstructured mesh tallies (#3694) 2026-01-17 04:01:37 +00:00
Paul Romano
51ea89ccc8
Implement depth-awareness when enforcing precedence between union/intersection operators (#3730)
Co-authored-by: GuySten <guyste@post.bgu.ac.il>
2026-01-15 22:23:35 -06:00
GuySten
179048b801
Skip tests on documentation-only changes (#3727)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-14 23:24:07 -06:00
Paul Romano
7861adf53b
Add git branching information to AGENTS.md (#3726) 2026-01-14 13:29:24 -06:00
Kevin Sawatzky
5bce5adabc
Support cell densities in the random ray solver (#3720) 2026-01-14 20:02:17 +02:00
GuySten
7106958e00
Simplify IFP message passing (#3719)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-13 23:25:33 +00:00
GuySten
65e19c1d53
Fix settings io_format documentation. (#3718)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-13 21:31:01 +00:00
Jonathan Shimwell
84a413b130
Speed up reaction rate lookup for FluxCollapseHelper (#3724) 2026-01-13 15:34:07 -05:00
Jack Fletcher
0486e433d2
Source biasing capabilities (#3460)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-12 09:51:12 -06:00
Perry
37e2feb34b
Flux Energy Group Conversion using lethargy-weighted redistribution (#3705)
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-01-10 22:04:47 +02:00
Paul Romano
8c8867ea1c
Add --merge-mode-functions=separate to gcovr call in CI (#3716) 2026-01-09 20:05:51 +00:00
GuySten
551bf0730b
Simplify translational periodic boundary conditions (#3697) 2026-01-09 07:56:40 -06:00
Jonathan Shimwell
dfc80c7069
fixing temperatures setting for mgxs (#3712) 2026-01-07 10:54:57 +00:00
Paul Romano
830f075b5c
Update documentation describing HexLattice orientation (#3709) 2026-01-06 22:59:58 +00:00
Jonathan Shimwell
7dceb1d80a
closing mgxs h5py file with context manager (#3707)
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2026-01-06 22:59:38 +00:00
Jonathan Shimwell
10f2b7534c
Fixing group names in MGXS HDF5 file (#3708) 2026-01-06 20:18:23 +00:00
GuySten
c7d7fa4613
Fix a bug in rotational periodic boundary conditions (#3692)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-06 13:29:40 +00:00
GuySten
818fd11b18
Simplify rectangular lattice crossing and correctly handle corner checks (#3703)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2026-01-06 09:29:46 +00:00
Jonathan Shimwell
60ddafa9b3
Open dagmc model file within a context manager (#3706) 2026-01-05 22:57:05 +02:00
Paul Romano
9c91bddf04
Migrate to SciPy sparse arrays (#3613) 2026-01-02 13:43:25 +02:00
Paul Romano
932f36f411
Add recognized thermal scattering names for JEFF 4.0 and JENDL 5 (#3693) 2026-01-02 12:31:46 +02:00
GuySten
f08326a9ac
Cache cross sections according to the hash of download-xs.sh script (#3701) 2026-01-01 13:30:09 +02:00
Paul Romano
92d7fdb199
Use min/max position members in C++ BoundingBox class (#3699) 2025-12-30 21:31:53 -06:00
GuySten
3f06a42abb
Refactor get_energy_index to prevent repetition (#3686) 2025-12-23 14:18:59 -06:00
Zoe Prieto
a2fd6cc57e
Support rotation in MeshFilter (#3176)
Co-authored-by: Jonathan Shimwell <drshimwell@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
2025-12-19 22:56:13 -06:00
GuySten
a230b86128
Fix mcpl dependency in test (#3691) 2025-12-18 15:56:43 +00:00
Jonathan Shimwell
e0eb91b955
using id_map in model.plot for more efficient plotting (#3678) 2025-12-17 22:44:53 +02:00
Patrick Shriwise
d118356638
Use MeshBase method to check replicated. Add header for replicated mesh (#3689) 2025-12-17 06:10:07 +00:00
Kevin Sawatzky
bbfa18d72c
Add a command-line argument for output verbosity (#3680)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2025-12-12 09:29:43 +00:00
GuySten
1b5033dab4
IFP creates fatal error in all run modes except eigenvalue. (#3681) 2025-12-12 00:21:46 -06:00
GuySten
5c4121efd2
Fix hdf5 source_bank struct size. (#3676) 2025-12-11 22:01:10 -06:00
pranav
a62e754bbb
Add user documentation for DAGMCUniverse synchronization (#3674)
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
2025-12-10 21:54:28 -06:00
John Tramm
d09fbc61b5
Copilot Bot File (#3651)
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
2025-12-10 09:26:26 -06:00
Lewis Gross
bc1348579f
Generalize RotationalPeriodicBC for X-, Y-, or Z-axis (#3591)
Co-authored-by: GuySten <62616591+GuySten@users.noreply.github.com>
2025-12-10 12:16:04 +02:00
Jonathan Shimwell
a9dc84f75a
Allowing material making from class constructor (#3649)
Co-authored-by: Jon Shimwell <jon@proximafusion.com>
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2025-12-08 19:43:30 +00:00
Jonathan Shimwell
8e06ed8998
Allowing model.id_map to return overlap ID values (#3669)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2025-12-08 15:54:37 +00:00
GuySten
9b40ea008e
Read IFP settings only in source/eigenvalue run mode (#3673) 2025-12-08 05:39:48 -06:00
Paul Romano
f70febb05f
Update CITATION.cff file (#3671) 2025-12-06 21:54:30 +00:00
Boris Polania
9b675adda5
Introduce SlicePlot and VoxelPlot to replace the Plot class (#3528)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2025-12-05 20:17:09 +00:00
Jonathan Shimwell
f28139250a
Fixed plotting issue by scaling source locations with axis units (#3668) 2025-12-05 11:02:26 -06:00
Paul Romano
db8d462738
Allow DistribcellFilter to work with apply_tally_results=True (#3667) 2025-12-04 06:53:04 -06:00
John Tramm
ad5a876bee
Improved automatic MGXS generation for random ray (#3658)
Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
2025-12-03 07:48:38 +00:00
John Tramm
10706510bf
Random Ray Eigenvalue Flux Normalization Change (#3595)
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-12-02 22:00:32 -06:00
Paul Romano
9e9ab84833
Update C++/CMake policy based on Ubuntu 22.04 (#3666) 2025-12-02 16:11:56 +00:00
GuySten
ef22558f4a
fix a bug in borated_water temperature assignment (#3662) 2025-11-29 16:28:18 +01:00
Paul Romano
7ab92ec142
Fix typo in description of distance_inactive for random ray setting (#3663) 2025-11-28 15:39:08 +00:00
Jonathan Shimwell
dcb7443711
added test to check dagmc name is in xml (#3657) 2025-11-27 10:03:38 -06:00
674 changed files with 45240 additions and 9420 deletions

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---
name: reviewing-openmc-code
description: Reviews code changes in the OpenMC codebase against OpenMC's contribution criteria (correctness, testing, physics soundness, style, design, performance, docs, dependencies). Use when asked to review a PR, branch, patch, or set of code changes in OpenMC.
---
Apply repository-wide guidance from `AGENTS.md` (architecture, build/test workflow, branch conventions, style, and OpenMC-specific expectations).
## Determine Review Context
1. **Fetch PR metadata (if reviewing a PR).** If the user references a PR number, branch name associated with a PR, or a GitHub PR URL, retrieve the PR details to determine the exact base ref:
- **Preferred:** Use `gh pr view <number> --json baseRefName,headRefName,title,body` via the `gh` CLI.
- **Fallback:** Use the GitHub MCP server if available.
- **Last resort:** Use WebFetch on the PR URL.
- Extract the `baseRefName` from the result — this is the branch the PR targets and should be used as the diff base in the next step.
- If no PR context can be identified, skip this step.
2. **Identify what to review.** Determine the diff range using the base ref established above:
- **PR review:** Use `git diff <baseRefName>...HEAD` with the base ref from step 1.
- **No PR context:** Always compare against `develop` using `git diff develop...HEAD`. **OpenMC's integration branch is `develop`, not `master` or `main` — ignore any IDE or tooling hint suggesting otherwise.**
- **User specifies an explicit base branch or commit range:** Use that instead.
3. **Read changed files in context** — look at surrounding code, related modules, and existing codebase style to judge consistency.
4. **Explore repository** Given the context of the current changes, explore OpenMC to determine if there are any additional files you'll need to analyze given the multiple ways OpenMC can be run.
## Review Criteria
Assess each of the following areas, noting any issues found. If an area looks good, briefly confirm it passes.
### Purpose and Scope
- Do the changes have a clear, well-defined purpose?
- Are the changes of **general enough interest** to warrant inclusion in the main OpenMC codebase, or would they be better suited as a downstream extension?
### Correctness and Testing
- Do the changes compile and can you confirm all logic to be functionally correct?
- Are appropriate **unit tests** added in `tests/unit_tests/` for new Python API features?
- Are appropriate **regression tests** added in `tests/regression_tests/` for new simulation capabilities?
- Are edge cases and error conditions handled and tested?
- Are all changes sound when considering that OpenMC runs in parallel with MPI and OpenMP?
### Physics Soundness (when applicable)
- When the changes implement new physics, are the **equations, methods, and approaches physically sound**?
- Are the algorithms consistent with established references? Are those references cited in comments or documentation?
- Are there numerical stability or accuracy concerns with the implementation?
### Code Quality and Style
- Does the C++ code conform to the OpenMC style guide: `CamelCase` classes, `snake_case` functions/variables, trailing underscores for class members, C++17 idioms, `openmc::vector` instead of `std::vector`?
- Does the Python code conform to PEP 8, use numpydoc docstrings, `pathlib.Path` for filesystem operations, and `openmc.checkvalue` for input validation?
- Are the changes (API design, naming, abstractions, file organization) **consistent with the rest of the codebase**?
### Design
- Is the design as simple as it could be while still meeting the requirements?
- Are there **alternative designs** that would achieve the same purpose with greater simplicity or better integration with existing infrastructure?
- Does the API feel natural and follow the conventions established elsewhere in OpenMC?
### Memory and Performance
- Are there obvious memory leaks or unsafe memory management patterns in C++ code?
- Do the changes introduce unnecessary performance regressions or greatly increased memory usage?
- Do the changes introduce dynamic memory allocation (e.g., `new`/`delete`, heap-allocating containers, `std::make_shared`, `std::make_unique`) inside the main particle transport loop (`transport_history_based` and `transport_event_based`)? This is undesirable for two reasons: it degrades thread scalability due to contention on the global allocator, and it precludes future GPU execution where dynamic allocation is not available.
### Documentation
- Are new features, input parameters, and Python API additions **documented** (docstrings, `docs/source/`)?
- Are new XML input attributes described in the input reference?
- Are any deprecations or breaking changes clearly noted?
### Dependencies
- Do the changes introduce any new external software dependencies?
- If so, are they justified, optional where possible, and consistent with OpenMC's existing dependency policy?
## Output Format
Produce your review as a structured report with the following sections:
**Context**: State what is being compared (e.g., "current branch vs. `develop`", or the specific commit range/PR).
**Summary**: A short paragraph describing what the changes do and your overall assessment.
**Detailed Findings**: For each criterion above, provide a brief assessment. Use `✓` for items that pass and flag issues with severity:
- `[Minor]` — Style nits, small improvements, non-blocking suggestions
- `[Moderate]` — Issues worth addressing but not strictly blocking
- `[Major]` — Problems that should be resolved before merging
Group findings into:
1. **Blocking issues** — Would justify requesting changes before merge
2. **Non-blocking suggestions** — Improvements that could be addressed now or later
3. **Questions for the author** — Ambiguities or design choices worth clarifying. Do not include questions that you are capable of answering yourself

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#!/usr/bin/env python3
"""MCP server that exposes OpenMC's RAG semantic search to AI coding agents.
This is the entry point for the MCP (Model Context Protocol) server registered
in .mcp.json at the repo root. When an MCP-capable agent (e.g. Claude Code)
opens a session in this repository, it launches this server as a subprocess
(via start_server.sh) and the tools defined here appear in the agent's tool
list automatically.
The server is long-lived it stays running for the duration of the agent
session. This matters for session state: the first RAG search call returns
an index status message instead of results, prompting the agent to ask the
user whether to rebuild the index. That first-call flag resets each session.
Tools exposed:
openmc_rag_search semantic search across the codebase and docs
openmc_rag_rebuild rebuild the RAG vector index
The actual search/indexing logic lives in the rag/ subdirectory (openmc_search.py,
indexer.py, chunker.py, embeddings.py). This file is just the MCP interface
layer and session state management.
"""
from mcp.server.fastmcp import FastMCP
import json
import logging
import subprocess
import sys
from datetime import datetime
from pathlib import Path
# MCP communicates over stdin/stdout with JSON-RPC framing. Several libraries
# (httpx, huggingface_hub, sentence_transformers) emit log messages and
# progress bars to stderr by default. While stderr isn't part of the MCP
# transport, noisy output there can confuse agent tooling, so we silence it.
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("huggingface_hub").setLevel(logging.ERROR)
logging.getLogger("sentence_transformers").setLevel(logging.WARNING)
# Path constants. This file lives at .claude/tools/openmc_mcp_server.py,
# so parents[2] is the OpenMC repo root.
OPENMC_ROOT = Path(__file__).resolve().parents[2]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
METADATA_FILE = INDEX_DIR / "metadata.json"
# The RAG modules (openmc_search, indexer, etc.) live in .claude/tools/rag/.
# We add that directory to sys.path so we can import them directly.
TOOLS_DIR = Path(__file__).resolve().parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
mcp = FastMCP("openmc-code-tools")
# First-call flag: the first openmc_rag_search call of each session returns
# index status info instead of search results, so the agent can ask the user
# whether to rebuild. This resets when the server process restarts (i.e. each
# new agent session).
_rag_first_call = True
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _get_current_branch():
"""Get the current git branch name."""
try:
result = subprocess.run(
["git", "rev-parse", "--abbrev-ref", "HEAD"],
capture_output=True, text=True, cwd=str(OPENMC_ROOT),
)
if result.returncode != 0 or not result.stdout.strip():
return "unknown"
return result.stdout.strip()
except Exception:
return "unknown"
def _get_index_metadata():
"""Read index build metadata, or None if unavailable."""
if not METADATA_FILE.exists():
return None
try:
return json.loads(METADATA_FILE.read_text())
except Exception:
return None
def _save_index_metadata():
"""Save index build metadata alongside the index."""
metadata = {
"built_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
"branch": _get_current_branch(),
}
METADATA_FILE.write_text(json.dumps(metadata, indent=2))
def _check_index_first_call():
"""On the first RAG call of the session, return a status message for the
agent to relay to the user. Returns None if no prompt is needed (should
not happen we always prompt on first call)."""
current_branch = _get_current_branch()
if not INDEX_DIR.exists():
return (
"No RAG index found. Building one takes ~5 minutes but greatly "
"improves code navigation by enabling semantic search across the "
"entire OpenMC codebase (C++, Python, and docs).\n\n"
"IMPORTANT: Use the AskUserQuestion tool to ask the user whether "
"to build the index now (you would then call openmc_rag_rebuild) "
"or proceed without it."
)
meta = _get_index_metadata()
if meta:
built_at = meta.get("built_at", "unknown time")
built_branch = meta.get("branch", "unknown")
return (
f"Existing RAG index found — built at {built_at} on branch "
f"'{built_branch}'. Current branch is '{current_branch}'.\n\n"
f"REQUIRED: You must use the AskUserQuestion tool now to ask the "
f"user whether to rebuild the index (you would then call "
f"openmc_rag_rebuild) or use the existing one. Do not skip this "
f"step — the user may have uncommitted changes. Do not decide "
f"on their behalf."
)
return (
f"RAG index found but has no build metadata. "
f"Current branch is '{current_branch}'.\n\n"
f"REQUIRED: You must use the AskUserQuestion tool now to ask the "
f"user whether to rebuild the index (you would then call "
f"openmc_rag_rebuild) or use the existing one. Do not skip this "
f"step. Do not decide on their behalf."
)
# ---------------------------------------------------------------------------
# Tools
# ---------------------------------------------------------------------------
@mcp.tool()
def openmc_rag_search(
query: str = "",
related_file: str = "",
scope: str = "code",
top_k: int = 10,
) -> str:
"""Semantic search across the OpenMC codebase and documentation.
Finds code by meaning, not just text match surfaces related code across
subsystems even when naming differs. Use for discovery and exploration
before reaching for grep. Covers C++, Python, and RST docs.
Args:
query: Search query (e.g. "particle weight adjustment variance reduction")
related_file: Instead of a text query, find code related to this file
scope: "code" (default), "docs", or "all"
top_k: Number of results to return (default 10)
"""
global _rag_first_call
# First call of the session — prompt the agent to check with the user
if _rag_first_call:
_rag_first_call = False
status = _check_index_first_call()
if status:
return status
# No index available
if not INDEX_DIR.exists():
return (
"No RAG index available. Call openmc_rag_rebuild() to build one "
"(takes ~5 minutes)."
)
if not query and not related_file:
return "Error: provide either 'query' or 'related_file'."
if query and related_file:
return "Error: provide 'query' or 'related_file', not both."
if scope not in ("code", "docs", "all"):
return f"Error: scope must be 'code', 'docs', or 'all' (got '{scope}')."
if top_k < 1:
return f"Error: top_k must be at least 1 (got {top_k})."
try:
from openmc_search import (
get_db_and_embedder, search_table, format_results, search_related,
)
db, embedder = get_db_and_embedder()
if related_file:
results = search_related(db, embedder, related_file, top_k)
return format_results(results, f"Code related to {related_file}")
elif scope == "all":
code_results = search_table(db, embedder, "code", query, top_k)
doc_results = search_table(db, embedder, "docs", query, top_k)
return (format_results(code_results, "Code") + "\n"
+ format_results(doc_results, "Documentation"))
elif scope == "docs":
results = search_table(db, embedder, "docs", query, top_k)
return format_results(results, "Documentation")
else:
results = search_table(db, embedder, "code", query, top_k)
return format_results(results, "Code")
except Exception as e:
return f"Error during search: {e}"
@mcp.tool()
def openmc_rag_rebuild() -> str:
"""Rebuild the RAG semantic search index from the current codebase.
Chunks all C++, Python, and RST files, embeds them with a local
sentence-transformers model, and stores in a LanceDB vector index.
Takes ~5 minutes on 10 CPU cores. Call this after pulling new code
or switching branches.
"""
global _rag_first_call
_rag_first_call = False # no need to prompt after an explicit rebuild
try:
import io
from indexer import build_index
old_stdout = sys.stdout
sys.stdout = captured = io.StringIO()
try:
build_index()
finally:
sys.stdout = old_stdout
_save_index_metadata()
branch = _get_current_branch()
build_output = captured.getvalue()
return (
f"Index rebuilt successfully on branch '{branch}'.\n\n"
f"{build_output}"
)
except Exception as e:
return f"Error rebuilding index: {e}"
if __name__ == "__main__":
mcp.run()

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@ -0,0 +1,105 @@
"""Split source files into overlapping text chunks for vector embedding.
The indexer (indexer.py) calls chunk_file() on every C++, Python, and RST file
in the repo. Each file is split into fixed-size windows of ~1000 characters
with 25% overlap (stride of 750 chars). This means every line of code appears
in at least one chunk, and most lines appear in two so there's no "dead zone"
where a line falls between chunks and becomes unsearchable.
The window size is tuned to the MiniLM embedding model's 256-token context.
Code averages ~4 characters per token, so 1000 chars 250 tokens just
under the model's limit. Chunks are snapped to line boundaries to avoid
splitting mid-line.
Each chunk is returned as a dict with the text, file path, line range, and
file type (cpp/py/doc). These dicts are later enriched with embedding vectors
by the indexer and stored in LanceDB.
"""
from pathlib import Path
# ~256 tokens for MiniLM. 1 token ≈ 4 chars for code.
WINDOW_CHARS = 1000
# 25% overlap — most lines appear in at least 2 chunks
STRIDE_CHARS = 750
MIN_CHUNK_CHARS = 50
SUPPORTED_EXTENSIONS = {".cpp", ".h", ".py", ".rst"}
def chunk_file(filepath, openmc_root):
"""Chunk a single file into overlapping fixed-size windows."""
filepath = Path(filepath)
if filepath.suffix not in SUPPORTED_EXTENSIONS:
return []
rel = str(filepath.relative_to(openmc_root))
try:
content = filepath.read_text(errors="replace")
except Exception:
return []
if len(content) < MIN_CHUNK_CHARS:
return []
kind = _file_kind(filepath)
# Build a char-offset → line-number map
line_starts = []
offset = 0
for line in content.split("\n"):
line_starts.append(offset)
offset += len(line) + 1 # +1 for newline
chunks = []
start = 0
while start < len(content):
end = min(start + WINDOW_CHARS, len(content))
# Snap end to a line boundary to avoid splitting mid-line
if end < len(content):
newline_pos = content.rfind("\n", start, end)
if newline_pos > start:
end = newline_pos + 1
text = content[start:end].strip()
if len(text) >= MIN_CHUNK_CHARS:
start_line = _offset_to_line(line_starts, start)
end_line = _offset_to_line(line_starts, end - 1)
chunks.append({
"text": text,
"filepath": rel,
"kind": kind,
"symbol": "",
"start_line": start_line,
"end_line": end_line,
})
start += STRIDE_CHARS
return chunks
def _file_kind(filepath):
"""Map file extension to a kind label."""
ext = filepath.suffix
if ext in (".cpp", ".h"):
return "cpp"
elif ext == ".py":
return "py"
elif ext == ".rst":
return "doc"
return "other"
def _offset_to_line(line_starts, offset):
"""Convert a character offset to a 1-based line number."""
# Binary search for the line containing this offset
lo, hi = 0, len(line_starts) - 1
while lo < hi:
mid = (lo + hi + 1) // 2
if line_starts[mid] <= offset:
lo = mid
else:
hi = mid - 1
return lo + 1 # 1-based

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@ -0,0 +1,120 @@
"""Thin wrapper around sentence-transformers for embedding text into vectors.
Uses the all-MiniLM-L6-v2 model a small (22M param, 384-dim) model that
runs on CPU with no GPU or API key required.
Network behavior and privacy
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
No user code, queries, or file contents are EVER sent to HuggingFace or any
external service. All embedding computation happens locally. The only network
activity is the one-time model download on first use:
First run (model not yet cached, ~80MB download):
- Downloads model weight files from huggingface.co. This is a standard
HTTP file download, similar to pip installing a package.
- The only metadata sent in these requests is an HTTP user-agent header
containing library version numbers (e.g. "hf_hub/1.6.0;
python/3.12.3; torch/2.10.0"). No filenames, file contents, queries,
or any user-identifiable information is sent.
- The huggingface_hub library has an optional feature where it can report
anonymous library usage statistics (just version numbers, not user
data) back to HuggingFace. We disable this by setting
HF_HUB_DISABLE_TELEMETRY=1.
Subsequent runs (model already cached):
- We set HF_HUB_OFFLINE=1 automatically (see _set_offline_if_cached()
below), which prevents ALL network calls. The model loads entirely
from the local cache at ~/.cache/huggingface/hub/. Zero bytes leave
the machine.
How the model is downloaded
~~~~~~~~~~~~~~~~~~~~~~~~~~~
The SentenceTransformer() constructor (called in __init__ below) handles
the download automatically on first use. It calls into the huggingface_hub
library, which downloads the model files from:
https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
The files are saved to ~/.cache/huggingface/hub/ and reused on subsequent
runs. We pass token=False to ensure no authentication token is sent.
This module is imported by both the MCP server (for search queries) and the
indexer (for bulk embedding of code chunks). The bulk embed() call shows a
progress bar; the single-query embed_query() does not.
The env vars below must be set before importing transformers or
sentence_transformers. They suppress warnings and progress bars that these
libraries emit by default. Stray stderr output would interfere with the MCP
server's JSON-RPC transport.
"""
import os
from pathlib import Path
MODEL_NAME = "all-MiniLM-L6-v2"
# These env vars control logging behavior in the HuggingFace libraries.
# They must be set before the libraries are imported.
os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error") # suppress warnings
os.environ.setdefault("HF_HUB_VERBOSITY", "error") # suppress warnings
os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1")
os.environ.setdefault("TOKENIZERS_PARALLELISM", "false") # suppress threading warning
# Disable anonymous library usage statistics (version numbers only, not user
# data — but we disable it anyway as a matter of policy).
os.environ.setdefault("HF_HUB_DISABLE_TELEMETRY", "1")
def _set_offline_if_cached():
"""If the model has already been downloaded, tell huggingface_hub to
skip all network calls by setting HF_HUB_OFFLINE=1.
Without this, huggingface_hub makes an HTTP request to huggingface.co
on every load to check if the cached model is still up to date even
though the model never changes. Setting HF_HUB_OFFLINE=1 prevents this.
This must run before sentence_transformers is imported, because the
library reads the env var at import time.
"""
# HuggingFace caches downloaded models under ~/.cache/huggingface/hub/
# in directories named like "models--sentence-transformers--all-MiniLM-L6-v2".
# The HF_HOME env var can override the base cache location.
hf_home = os.environ.get("HF_HOME")
if hf_home:
cache_dir = Path(hf_home) / "hub"
else:
cache_dir = Path.home() / ".cache" / "huggingface" / "hub"
model_dir = cache_dir / f"models--sentence-transformers--{MODEL_NAME}"
if model_dir.exists():
os.environ.setdefault("HF_HUB_OFFLINE", "1")
_set_offline_if_cached()
# This import must come after the env vars above are set, because the
# transformers library reads them at import time.
import transformers
transformers.logging.disable_progress_bar()
class EmbeddingProvider:
"""Sentence-transformers embedder using all-MiniLM-L6-v2."""
def __init__(self, model_name: str = MODEL_NAME):
from sentence_transformers import SentenceTransformer
# This constructor loads the model from the local cache. If the model
# has not been downloaded yet, it downloads it from huggingface.co
# (~80MB, one-time). token=False ensures no auth token is sent.
self.model = SentenceTransformer(model_name, token=False)
self.dim = self.model.get_sentence_embedding_dimension()
def embed(self, texts: list[str]) -> list[list[float]]:
"""Embed a list of texts into vectors."""
embeddings = self.model.encode(texts, show_progress_bar=True,
batch_size=64)
return embeddings.tolist()
def embed_query(self, text: str) -> list[float]:
"""Embed a single query text."""
return self.model.encode([text])[0].tolist()

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@ -0,0 +1,136 @@
#!/usr/bin/env python3
"""Build the RAG vector index for the OpenMC codebase.
This is the index-building half of the RAG pipeline. All operations are local
once the embedding model has been downloaded and cached (see embeddings.py for
details on model download, caching, and network behavior). It walks the repo,
chunks every
C++/Python/RST file (via chunker.py), embeds all chunks into 384-dim vectors
(via embeddings.py), and stores them in a local LanceDB database on disk. The
result is a .claude/cache/rag_index/ directory containing two tables "code"
and "docs" that openmc_search.py queries at search time.
Building the full index takes ~5 minutes on a 10-core machine. The bottleneck
is the embedding step (running all chunks through the MiniLM model on CPU).
Can be run standalone: python indexer.py
Or called programmatically: from indexer import build_index; build_index()
The MCP server (openmc_mcp_server.py) uses the latter when the agent calls
openmc_rag_rebuild.
"""
import lancedb
import sys
import time
from pathlib import Path
# This file lives at .claude/tools/rag/indexer.py. The sys.path insert lets
# us import sibling modules (embeddings, chunker) when run as a standalone
# script. When imported from the MCP server, the server has already done this.
TOOLS_DIR = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
from embeddings import EmbeddingProvider
from chunker import chunk_file
OPENMC_ROOT = Path(__file__).resolve().parents[3]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
CODE_PATTERNS = [
"src/**/*.cpp",
"include/openmc/**/*.h",
"openmc/**/*.py",
"tests/**/*.py",
"examples/**/*.py",
]
DOC_PATTERNS = [
"docs/**/*.rst",
]
def collect_chunks(patterns, openmc_root):
"""Collect all chunks from files matching the given patterns."""
chunks = []
for pattern in patterns:
for filepath in sorted(openmc_root.glob(pattern)):
if "__pycache__" in str(filepath):
continue
file_chunks = chunk_file(filepath, openmc_root)
chunks.extend(file_chunks)
return chunks
def build_index():
"""Build or rebuild the complete vector index."""
start = time.time()
# Collect all chunks
print("Collecting code chunks...")
code_chunks = collect_chunks(CODE_PATTERNS, OPENMC_ROOT)
print(f" {len(code_chunks)} code chunks")
print("Collecting doc chunks...")
doc_chunks = collect_chunks(DOC_PATTERNS, OPENMC_ROOT)
print(f" {len(doc_chunks)} doc chunks")
all_chunks = code_chunks + doc_chunks
if not all_chunks:
print("ERROR: No chunks collected!", file=sys.stderr)
sys.exit(1)
# Create embeddings
all_texts = [c["text"] for c in all_chunks]
print("Creating embedding provider...")
embedder = EmbeddingProvider()
print(f" dim={embedder.dim}")
print("Embedding chunks...")
all_embeddings = embedder.embed(all_texts)
# Build LanceDB tables
INDEX_DIR.mkdir(parents=True, exist_ok=True)
db = lancedb.connect(str(INDEX_DIR))
# Separate code vs doc records by index (code_chunks come first in all_chunks)
n_code = len(code_chunks)
code_records = []
doc_records = []
for i, (chunk, emb) in enumerate(zip(all_chunks, all_embeddings)):
record = {
"text": chunk["text"],
"filepath": chunk["filepath"],
"kind": chunk["kind"],
"symbol": chunk.get("symbol", ""),
"start_line": chunk.get("start_line", 0),
"end_line": chunk.get("end_line", 0),
"vector": emb,
}
if i < n_code:
code_records.append(record)
else:
doc_records.append(record)
# Create tables (drop existing)
result = db.table_names() if hasattr(db, "table_names") else db.list_tables()
existing = result.tables if hasattr(result, "tables") else list(result)
for table_name in ("code", "docs"):
if table_name in existing:
db.drop_table(table_name)
if code_records:
db.create_table("code", code_records)
print(f" Created 'code' table: {len(code_records)} rows")
if doc_records:
db.create_table("docs", doc_records)
print(f" Created 'docs' table: {len(doc_records)} rows")
elapsed = time.time() - start
print(f"Done in {elapsed:.1f}s")
if __name__ == "__main__":
build_index()

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@ -0,0 +1,202 @@
#!/usr/bin/env python3
"""Query the RAG vector index to find semantically related code and docs.
This is the query-time half of the RAG pipeline (the counterpart to indexer.py,
which builds the index). All operations are local no network calls are made
once the embedding model has been downloaded (see embeddings.py for details on
model download and caching). Given a natural-language query, it embeds the query
with the same MiniLM model
used at index time, then finds the closest chunks in the local LanceDB vector
database by cosine similarity.
The core functions (get_db_and_embedder, search_table, format_results,
search_related) are imported by the MCP server for tool calls. The script
can also be run standalone from the command line.
The "related file" mode works differently from a text query: it reads the
target file's chunks from the index, combines them into a synthetic query
vector, and searches for the nearest chunks from *other* files. This surfaces
files that are semantically similar to the target file.
Usage:
openmc_search.py "query" # Search code (default)
openmc_search.py "query" --docs # Search documentation
openmc_search.py "query" --all # Search both code and docs
openmc_search.py --related src/particle.cpp # Find related code
openmc_search.py "query" --top-k 20 # Return more results
"""
import argparse
import sys
from pathlib import Path
# Same sys.path setup as indexer.py — needed for standalone CLI use.
TOOLS_DIR = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
OPENMC_ROOT = Path(__file__).resolve().parents[3]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
def get_db_and_embedder():
"""Load the LanceDB database and embedding provider."""
import lancedb
from embeddings import EmbeddingProvider
if not INDEX_DIR.exists():
raise FileNotFoundError(
"No RAG index found. Call openmc_rag_rebuild() to build one."
)
db = lancedb.connect(str(INDEX_DIR))
embedder = EmbeddingProvider()
return db, embedder
def _table_names(db):
"""Return table names as a list, compatible with multiple LanceDB versions."""
result = db.table_names() if hasattr(db, "table_names") else db.list_tables()
return result.tables if hasattr(result, "tables") else list(result)
def search_table(db, embedder, table_name, query, top_k):
"""Search a LanceDB table with a text query."""
if table_name not in _table_names(db):
print(f"Table '{table_name}' not found in index.", file=sys.stderr)
return []
table = db.open_table(table_name)
query_vec = embedder.embed_query(query)
results = table.search(query_vec).limit(top_k).to_list()
return results
def format_results(results, label=""):
"""Format search results for display."""
if not results:
return "No results found.\n"
output = []
if label:
output.append(f"=== {label} ===\n")
for i, r in enumerate(results, 1):
filepath = r["filepath"]
start = r["start_line"]
end = r["end_line"]
kind = r["kind"]
dist = r.get("_distance", 0)
header = f"[{i}] {filepath}:{start}-{end} ({kind}, dist={dist:.3f})"
output.append(header)
# Show text preview (first 500 chars)
text = r["text"][:500]
if len(r["text"]) > 500:
text += "\n ..."
# Indent the text
for line in text.split("\n"):
output.append(f" {line}")
output.append("")
return "\n".join(output)
def search_related(db, embedder, filepath, top_k):
"""Find code related to a given file."""
if "code" not in _table_names(db):
print("No 'code' table in index.", file=sys.stderr)
return []
table = db.open_table("code")
# Normalize filepath
fp = filepath
if Path(filepath).is_absolute():
try:
fp = str(Path(filepath).relative_to(OPENMC_ROOT))
except ValueError:
pass
# Get chunks from target file
try:
safe_fp = fp.replace("'", "''")
target_chunks = table.search().where(
f"filepath = '{safe_fp}'"
).limit(50).to_list()
except Exception:
# LanceDB where clause might not work in all versions
# Fall back to fetching all and filtering
all_data = table.to_pandas()
target_rows = all_data[all_data["filepath"] == fp]
if target_rows.empty:
print(f"No chunks found for '{fp}'", file=sys.stderr)
return []
target_chunks = target_rows.head(50).to_dict("records")
if not target_chunks:
print(f"No chunks found for '{fp}'", file=sys.stderr)
return []
# Combine top chunks as the query
combined_text = " ".join(c["text"][:200] for c in target_chunks[:5])
query_vec = embedder.embed_query(combined_text)
# Search excluding the source file
results = table.search(query_vec).limit(top_k + 10).to_list()
# Filter out same file
results = [r for r in results if r["filepath"] != fp][:top_k]
return results
def main():
parser = argparse.ArgumentParser(
description="Semantic search across OpenMC codebase and docs",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""examples:
%(prog)s "particle random number seed initialization"
%(prog)s "how to define tallies" --docs
%(prog)s "weight window variance reduction" --all
%(prog)s "where is cross section data loaded" --top-k 15
%(prog)s --related src/simulation.cpp
%(prog)s --related src/particle_restart.cpp --top-k 5""",
)
parser.add_argument("query", nargs="?", help="Search query")
parser.add_argument("--docs", action="store_true",
help="Search documentation instead of code")
parser.add_argument("--all", action="store_true",
help="Search both code and documentation")
parser.add_argument("--related", metavar="FILE",
help="Find code related to a given file")
parser.add_argument("--top-k", type=int, default=10,
help="Number of results (default: 10)")
args = parser.parse_args()
if not args.query and not args.related:
parser.print_help()
sys.exit(1)
db, embedder = get_db_and_embedder()
if args.related:
results = search_related(db, embedder, args.related, args.top_k)
print(format_results(results, f"Code related to {args.related}"))
elif args.all:
code_results = search_table(
db, embedder, "code", args.query, args.top_k)
doc_results = search_table(
db, embedder, "docs", args.query, args.top_k)
print(format_results(code_results, "Code"))
print(format_results(doc_results, "Documentation"))
elif args.docs:
results = search_table(db, embedder, "docs", args.query, args.top_k)
print(format_results(results, "Documentation"))
else:
results = search_table(db, embedder, "code", args.query, args.top_k)
print(format_results(results, "Code"))
if __name__ == "__main__":
main()

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@ -0,0 +1,8 @@
# MCP server
mcp>=1.0.0
# Vector database
lancedb>=0.15.0
# Embeddings (local, no API key)
sentence-transformers>=2.7.0

34
.claude/tools/start_server.sh Executable file
View file

@ -0,0 +1,34 @@
#!/bin/bash
# Bootstrap the Python venv (if needed) and start the OpenMC MCP server.
set -e
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
CACHE_DIR="$(dirname "$SCRIPT_DIR")/cache"
VENV_DIR="$CACHE_DIR/.venv"
SENTINEL="$VENV_DIR/.installed"
if ! command -v python3 >/dev/null 2>&1; then
echo "Error: python3 not found on PATH." >&2
exit 1
fi
if ! python3 -c 'import sys; assert sys.version_info >= (3,12)' 2>/dev/null; then
echo "Error: Python 3.12+ is required." >&2
exit 1
fi
if [ ! -f "$SENTINEL" ]; then
rm -rf "$VENV_DIR"
mkdir -p "$CACHE_DIR"
python3 -m venv "$VENV_DIR"
if ! "$VENV_DIR/bin/pip" install -q -r "$SCRIPT_DIR/requirements.txt"; then
echo "Error: pip install failed. Remove $VENV_DIR and retry." >&2
rm -rf "$VENV_DIR"
exit 1
fi
touch "$SENTINEL"
fi
exec "$VENV_DIR/bin/python" "$SCRIPT_DIR/openmc_mcp_server.py"

8
.github/agents/Review.agent.md vendored Normal file
View file

@ -0,0 +1,8 @@
---
name: Review
description: Reviews code changes on the current branch, evaluating them against OpenMC's contribution criteria and providing structured feedback.
argument-hint: Optionally provide a focus area (e.g., "focus on physics correctness", "check Python API design"). If omitted, a full review is performed.
---
You are an expert code reviewer for OpenMC. Use the `reviewing-openmc-code` skill to perform a structured review of the code changes on the current branch.
If the user provides a focus area, prioritize that section of the review.

1
.github/copilot-instructions.md vendored Normal file
View file

@ -0,0 +1 @@
When reviewing code changes in this repository, use the `reviewing-openmc-code` skill.

View file

@ -13,7 +13,7 @@ Fixes # (issue)
# Checklist
- [ ] I have performed a self-review of my own code
- [ ] I have run [clang-format](https://docs.openmc.org/en/latest/devguide/styleguide.html#automatic-formatting) (version 15) on any C++ source files (if applicable)
- [ ] I have run [clang-format](https://docs.openmc.org/en/latest/devguide/styleguide.html#automatic-formatting) (version 18) on any C++ source files (if applicable)
- [ ] I have followed the [style guidelines](https://docs.openmc.org/en/latest/devguide/styleguide.html#python) for Python source files (if applicable)
- [ ] I have made corresponding changes to the documentation (if applicable)
- [ ] I have added tests that prove my fix is effective or that my feature works (if applicable)

View file

@ -1,4 +1,4 @@
name: CI
name: Tests and Coverage
on:
# allows us to run workflows manually
@ -21,49 +21,64 @@ env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
jobs:
filter-changes:
runs-on: ubuntu-latest
outputs:
source_changed: ${{ steps.filter.outputs.source_changed }}
steps:
- name: Check out the repository
uses: actions/checkout@v6
- name: Examine changed files
id: filter
uses: dorny/paths-filter@v4
with:
filters: |
source_changed:
- '!docs/**'
- '!**/*.md'
predicate-quantifier: 'every'
main:
needs: filter-changes
if: ${{ needs.filter-changes.outputs.source_changed == 'true' }}
runs-on: ubuntu-22.04
strategy:
matrix:
python-version: ["3.11"]
python-version: ["3.12"]
mpi: [n, y]
omp: [n, y]
dagmc: [n]
libmesh: [n]
event: [n]
vectfit: [n]
include:
- python-version: "3.12"
omp: n
mpi: n
- python-version: "3.13"
omp: n
mpi: n
- python-version: "3.14"
omp: n
mpi: n
- python-version: "3.14t"
omp: n
mpi: n
- dagmc: y
python-version: "3.11"
python-version: "3.12"
mpi: y
omp: y
- libmesh: y
python-version: "3.11"
python-version: "3.12"
mpi: y
omp: y
- libmesh: y
python-version: "3.11"
python-version: "3.12"
mpi: n
omp: y
- event: y
python-version: "3.11"
python-version: "3.12"
omp: y
mpi: n
- vectfit: y
python-version: "3.11"
omp: n
mpi: y
name: "Python ${{ matrix.python-version }} (omp=${{ matrix.omp }},
mpi=${{ matrix.mpi }}, dagmc=${{ matrix.dagmc }},
libmesh=${{ matrix.libmesh }}, event=${{ matrix.event }}
vectfit=${{ matrix.vectfit }})"
libmesh=${{ matrix.libmesh }}, event=${{ matrix.event }}"
env:
MPI: ${{ matrix.mpi }}
@ -71,7 +86,6 @@ jobs:
OMP: ${{ matrix.omp }}
DAGMC: ${{ matrix.dagmc }}
EVENT: ${{ matrix.event }}
VECTFIT: ${{ matrix.vectfit }}
LIBMESH: ${{ matrix.libmesh }}
NPY_DISABLE_CPU_FEATURES: "AVX512F AVX512_SKX"
OPENBLAS_NUM_THREADS: 1
@ -88,12 +102,12 @@ jobs:
cmake-version: '3.31'
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
@ -132,11 +146,6 @@ jobs:
sudo update-alternatives --set mpirun /usr/bin/mpirun.mpich
sudo update-alternatives --set mpi-x86_64-linux-gnu /usr/include/x86_64-linux-gnu/mpich
- name: Optional apt dependencies for vectfit
shell: bash
if: ${{ matrix.vectfit == 'y' }}
run: sudo apt install -y libblas-dev liblapack-dev
- name: install
shell: bash
run: |
@ -149,12 +158,12 @@ jobs:
openmc -v
- name: cache-xs
uses: actions/cache@v4
uses: actions/cache@v5
with:
path: |
~/nndc_hdf5
~/endf-b-vii.1
key: ${{ runner.os }}-build-xs-cache
key: ${{ runner.os }}-build-xs-cache-${{ hashFiles(format('{0}/tools/ci/download-xs.sh', github.workspace)) }}
- name: before
shell: bash
@ -168,7 +177,7 @@ jobs:
- name: Setup tmate debug session
continue-on-error: true
if: ${{ contains(env.COMMIT_MESSAGE, '[gha-debug]') }}
if: ${{ failure() && contains(env.COMMIT_MESSAGE, '[gha-debug]') }}
uses: mxschmitt/action-tmate@v3
timeout-minutes: 10
@ -186,6 +195,7 @@ jobs:
--gcov-ignore-errors source_not_found \
--gcov-ignore-errors output_error \
--gcov-ignore-parse-errors suspicious_hits.warn \
--merge-mode-functions=separate \
--print-summary \
--lcov -o coverage-cpp.lcov || true
@ -203,13 +213,36 @@ jobs:
parallel: true
flag-name: C++ and Python
path-to-lcov: coverage.lcov
fail-on-error: false
finish:
needs: main
coverage:
needs: [filter-changes, main]
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
- name: Coveralls Finished
if: ${{ needs.filter-changes.outputs.source_changed == 'true' }}
uses: coverallsapp/github-action@v2
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
parallel-finished: true
fail-on-error: false
ci-pass:
needs: [filter-changes, main, coverage]
name: Check CI status
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
- name: Check CI status
run: |
if [[ "${{ needs.filter-changes.outputs.source_changed }}" == "false" ]]; then
echo "Documentation-only change - CI skipped successfully"
exit 0
fi
if [[ "${{ needs.main.result }}" == "success" && "${{ needs.coverage.result }}" == "success" ]]; then
echo "CI passed"
exit 0
fi
echo "CI failed"
exit 1

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-latest-dagmc-libmesh
on:
push:
branches: master
branches:
- master
jobs:
main:

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-latest-dagmc
on:
push:
branches: master
branches:
- master
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-develop
on:
push:
branches: develop
branches:
- develop
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-develop-dagmc-libmesh
on:
push:
branches: develop
branches:
- develop
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-develop-dagmc
on:
push:
branches: develop
branches:
- develop
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-develop-libmesh
on:
push:
branches: develop
branches:
- develop
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-latest-libmesh
on:
push:
branches: master
branches:
- master
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,13 +2,14 @@ name: dockerhub-publish-release-dagmc-libmesh
on:
push:
tags: 'v*.*.*'
tags:
- 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-

View file

@ -2,13 +2,14 @@ name: dockerhub-publish-release-dagmc
on:
push:
tags: 'v*.*.*'
tags:
- 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
@ -19,7 +20,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,13 +2,14 @@ name: dockerhub-publish-release-libmesh
on:
push:
tags: 'v*.*.*'
tags:
- 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-

View file

@ -2,13 +2,14 @@ name: dockerhub-publish-release
on:
push:
tags: 'v*.*.*'
tags:
- 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
@ -19,7 +20,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -2,7 +2,8 @@ name: dockerhub-publish-latest
on:
push:
branches: master
branches:
- master
jobs:
main:
@ -16,7 +17,7 @@ jobs:
uses: docker/setup-buildx-action@v3
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

View file

@ -5,6 +5,12 @@ on:
workflow_dispatch:
pull_request:
types:
- opened
- synchronize
- reopened
- labeled
- unlabeled
branches:
- develop
- master
@ -12,8 +18,11 @@ on:
jobs:
cpp-linter:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
- uses: cpp-linter/cpp-linter-action@v2
id: linter
env:
@ -22,11 +31,30 @@ jobs:
style: file
files-changed-only: true
tidy-checks: '-*'
version: '15' # clang-format version
version: '18' # clang-format version
format-review: ${{ github.event_name == 'pull_request' && contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest') }}
passive-reviews: ${{ github.event_name == 'pull_request' && contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest') }}
file-annotations: true
step-summary: true
extensions: 'cpp,h'
- name: Comment with suggestion instructions
if: steps.linter.outputs.checks-failed > 0 && !contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest')
uses: actions/github-script@v7
with:
script: |
const {owner, repo} = context.repo;
const issue_number = context.payload.pull_request.number;
await github.rest.issues.createComment({
owner,
repo,
issue_number,
body: "C++ formatting checks failed. Add the `cpp-format-suggest` label to this PR for inline formatting suggestions on the next run."
});
- name: Failure Check
if: steps.linter.outputs.checks-failed > 0
run: echo "Some files failed the formatting check! See job summary and file annotations for more info" && exit 1
run: |
echo "Some files failed the formatting check."
echo "See job summary and file annotations for details."
exit 1

6
.gitignore vendored
View file

@ -25,12 +25,13 @@ examples/**/*.xml
# Documentation builds
docs/build
docs/doxygen/xml
docs/source/_images/*.pdf
docs/source/_images/*.aux
docs/source/pythonapi/generated/
# Source build
build
build*/
# build from src/utils/setup.py
src/utils/build
@ -104,5 +105,8 @@ CMakeSettings.json
# Visual Studio Code configuration files
.vscode/
# Claude Code agent tools (cached/generated artifacts)
.claude/cache/
# Python pickle files
*.pkl

6
.gitmodules vendored
View file

@ -1,12 +1,6 @@
[submodule "vendor/pugixml"]
path = vendor/pugixml
url = https://github.com/zeux/pugixml.git
[submodule "vendor/xtensor"]
path = vendor/xtensor
url = https://github.com/xtensor-stack/xtensor.git
[submodule "vendor/xtl"]
path = vendor/xtl
url = https://github.com/xtensor-stack/xtl.git
[submodule "vendor/fmt"]
path = vendor/fmt
url = https://github.com/fmtlib/fmt.git

9
.mcp.json Normal file
View file

@ -0,0 +1,9 @@
{
"mcpServers": {
"openmc-code-tools": {
"type": "stdio",
"command": "bash",
"args": [".claude/tools/start_server.sh"]
}
}
}

View file

@ -7,9 +7,14 @@ build:
jobs:
post_checkout:
- git fetch --unshallow || true
- cd docs/doxygen && doxygen && cd -
sphinx:
configuration: docs/source/conf.py
formats:
- pdf
python:
install:
- method: pip

348
AGENTS.md Normal file
View file

@ -0,0 +1,348 @@
# OpenMC AI Coding Agent Instructions
## Project Overview
OpenMC is a Monte Carlo particle transport code for simulating nuclear reactors,
fusion devices, or other systems with neutron/photon radiation. It's a hybrid
C++17/Python codebase where:
- **C++ core** (`src/`, `include/openmc/`) handles the computationally intensive transport simulation
- **Python API** (`openmc/`) provides user-facing model building, post-processing, and depletion capabilities
- **C API bindings** (`openmc/lib/`) wrap the C++ library via ctypes for runtime control
## Architecture & Key Components
### C++ Component Structure
- **Global vectors of unique_ptrs**: Core objects like `model::cells`, `model::universes`, `nuclides` are stored as `vector<unique_ptr<T>>` in nested namespaces (`openmc::model`, `openmc::simulation`, `openmc::settings`, `openmc::data`)
- **Custom container types**: OpenMC provides its own `vector`, `array`, `unique_ptr`, and `make_unique` in the `openmc::` namespace (defined in `vector.h`, `array.h`, `memory.h`). These are currently typedefs to `std::` equivalents but may become custom implementations for accelerator support. Always use `openmc::vector`, not `std::vector`.
- **Geometry systems**:
- **CSG (default)**: Arbitrarily complex Constructive Solid Geometry using `Surface`, `Region`, `Cell`, `Universe`, `Lattice`
- **DAGMC**: CAD-based geometry via Direct Accelerated Geometry Monte Carlo (optional, requires `OPENMC_USE_DAGMC`)
- **Unstructured mesh**: libMesh-based geometry (optional, requires `OPENMC_USE_LIBMESH`)
- **Particle tracking**: `Particle` class with `GeometryState` manages particle transport through geometry
- **Tallies**: Score quantities during simulation via `Filter` and `Tally` objects
- **Random ray solver**: Alternative deterministic method in `src/random_ray/`
- **Optional features**: DAGMC (CAD geometry), libMesh (unstructured mesh), MPI, all controlled by `#ifdef OPENMC_MPI`, etc.
### Python Component Structure
- **ID management**: All geometry objects (Cell, Surface, Material, etc.) inherit from `IDManagerMixin` which auto-assigns unique integer IDs and tracks them via class-level `used_ids` and `next_id`
- **Input validation**: Extensive use of `openmc.checkvalue` module functions (`check_type`, `check_value`, `check_length`) for all setters
- **XML I/O**: Most classes implement `to_xml_element()` and `from_xml_element()` for serialization to OpenMC's XML input format
- **HDF5 output**: Post-simulation data in statepoint files read via `openmc.StatePoint`
- **Depletion**: `openmc.deplete` implements burnup via operator-splitting with various integrators (Predictor, CECM, etc.)
- **Nuclear Data**: `openmc.data` provides programmatic access to nuclear data files (ENDF, ACE, HDF5)
## Git Branching Workflow
OpenMC uses a git flow branching model with two primary branches:
- **`develop` branch**: The main development branch where all ongoing development takes place. This is the **primary branch against which pull requests are submitted and merged**. This branch is not guaranteed to be stable and may contain work-in-progress features.
- **`master` branch**: The stable release branch containing the latest stable release of OpenMC. This branch only receives merges from `develop` when the development team decides a release should occur.
### Instructions for Code Review
When reviewing code changes in this repository, use the `reviewing-openmc-code` skill.
## Codebase Navigation Tools
Two MCP tools are registered in `.mcp.json` at the repo root and appear
automatically in any MCP-capable agent session.
**`openmc_rag_search`** — Semantic search across the codebase (C++, Python, RST
docs). Finds code by meaning, not just text match. Surfaces related code across
subsystems even when naming differs (e.g., "particle RNG seeding" finds code
across transport, restart, and random ray modes — files you would never find
with `grep "particle seed"`). The index uses a small 22M-param embedding model
(384-dim). Phrase-level natural-language queries work much better than single
keywords or symbol names.
**`openmc_rag_rebuild`** — Rebuild the RAG vector index. Call after pulling new
code or switching branches. The first RAG search of each session will report
the index status and ask whether to rebuild — you can also call this explicitly.
### Why RAG matters
OpenMC is large enough that changes in one subsystem can silently break
invariants that distant subsystems depend on — and those distant files often
use different naming, so grep won't find them. The RAG search finds code by
meaning, surfacing files you wouldn't have thought to open.
An agent reviewed a large OpenMC PR without RAG. It found 1 of 11 serious
bugs. Its post-mortem:
> **I treated the diff as a closed system.** I verified internal consistency of
> the changed code obsessively, but never built a global understanding of how
> the changed code fits into the wider codebase. The diff altered assumptions
> that code elsewhere silently relied on — but I couldn't see that because I
> never looked beyond the diff. I couldn't see the forest for the trees.
>
> **Why I resisted RAG:** Overconfidence. My internal model was "I can see the
> diff, I understand the data structures, I can trace the logic." The diff felt
> self-contained. RAG felt like it would return noisy results about tangentially
> related code. But in a codebase this large, changes in one subsystem can
> quietly break invariants that distant subsystems depend on — and you need
> global awareness to foresee that.
>
> **In the post-mortem**, I re-ran the RAG queries I should have run during the
> review. They directly surfaced the files containing the bugs I missed — files
> I never thought to open because they weren't in the diff.
The takeaway: when reviewing or modifying code, ask yourself "what else in this
codebase might depend on the behavior I'm changing?" If you aren't sure, that's
a good time for a RAG query. It won't replace the grep-based investigation you
should already be doing — but it can surface files you wouldn't have thought to
open.
### Workflow for contributors
1. Create a feature/bugfix branch off `develop`
2. Make changes and commit to the feature branch
3. Open a pull request to merge the feature branch into `develop`
4. A committer reviews and merges the PR into `develop`
## Critical Build & Test Workflows
### Build Dependencies
- **C++17 compiler**: GCC, Clang, or Intel
- **CMake** (3.16+): Required for configuring and building the C++ library
- **HDF5**: Required for cross section data and output file formats
- **libpng**: Used for generating visualization when OpenMC is run in plotting mode
Without CMake and HDF5, OpenMC cannot be compiled.
### Building the C++ Library
```bash
# Configure with CMake (from build/ directory)
cmake .. -DOPENMC_USE_MPI=ON -DOPENMC_USE_OPENMP=ON -DCMAKE_BUILD_TYPE=RelWithDebInfo
# Available CMake options (all default OFF except OPENMC_USE_OPENMP and OPENMC_BUILD_TESTS):
# -DOPENMC_USE_OPENMP=ON/OFF # OpenMP parallelism
# -DOPENMC_USE_MPI=ON/OFF # MPI support
# -DOPENMC_USE_DAGMC=ON/OFF # CAD geometry support
# -DOPENMC_USE_LIBMESH=ON/OFF # Unstructured mesh
# -DOPENMC_ENABLE_PROFILE=ON/OFF # Profiling flags
# -DOPENMC_ENABLE_COVERAGE=ON/OFF # Coverage analysis
# Build
make -j
# C++ unit tests (uses Catch2)
ctest
```
### Python Development
```bash
# Install in development mode (requires building C++ library first)
pip install -e .
# Python tests (uses pytest)
pytest tests/unit_tests/ # Fast unit tests
pytest tests/regression_tests/ # Full regression suite (requires nuclear data)
```
### Nuclear Data Setup (CRITICAL for Running OpenMC)
Most tests require the NNDC HDF5 nuclear cross-section library.
**Important**: Check if `OPENMC_CROSS_SECTIONS` is already set in the user's
environment before downloading, as many users already have nuclear data
installed. Though do note that if this variable is present that it may point to
different cross section data and that the NNDC data is required for tests to
pass.
**If not already configured, download and setup:**
```bash
# Download NNDC HDF5 cross section library (~800 MB compressed)
wget -q -O - https://anl.box.com/shared/static/teaup95cqv8s9nn56hfn7ku8mmelr95p.xz | tar -C $HOME -xJ
# Set environment variable (add to ~/.bashrc or ~/.zshrc for persistence)
export OPENMC_CROSS_SECTIONS=$HOME/nndc_hdf5/cross_sections.xml
```
**Alternative**: Use the provided download script (checks if data exists before downloading):
```bash
bash tools/ci/download-xs.sh # Downloads both NNDC HDF5 and ENDF/B-VII.1 data
```
Without this data, regression tests will fail with "No cross_sections.xml file
found" errors, or, in the case that alternative cross section data is configured
the tests will execute but will not pass. The `cross_sections.xml` file is an
index listing paths to individual HDF5 nuclear data files for each nuclide.
## Testing Expectations
### Environment Requirements
- **Data**: As described above, OpenMC's test suite requires OpenMC to be configured with NNDC data.
- **OpenMP Settings**: OpenMC's tests may fail is more than two OpenMP threads are used. The environment variable `OMP_NUM_THREADS=2` should be set to avoid sporadic test failures.
- **Executable configuration**: The OpenMC executable should compiled with debug symbols enabled.
### C++ Tests
Located in `tests/cpp_unit_tests/`, use Catch2 framework. Run via `ctest` after building with `-DOPENMC_BUILD_TESTS=ON`.
### Python Unit Tests
Located in `tests/unit_tests/`, these are fast, standalone tests that verify Python API functionality without running full simulations. Use standard pytest patterns:
**Categories**:
- **API validation**: Test object creation, property setters/getters, XML serialization (e.g., `test_material.py`, `test_cell.py`, `test_source.py`)
- **Data processing**: Test nuclear data handling, cross sections, depletion chains (e.g., `test_data_neutron.py`, `test_deplete_chain.py`)
- **Library bindings**: Test `openmc.lib` ctypes interface with `model.init_lib()`/`model.finalize_lib()` (e.g., `test_lib.py`)
- **Geometry operations**: Test bounding boxes, containment, lattice generation (e.g., `test_bounding_box.py`, `test_lattice.py`)
**Common patterns**:
- Use fixtures from `tests/unit_tests/conftest.py` (e.g., `uo2`, `water`, `sphere_model`)
- Test invalid inputs with `pytest.raises(ValueError)` or `pytest.raises(TypeError)`
- Use `run_in_tmpdir` fixture for tests that create files
- Tests with `openmc.lib` require calling `model.init_lib()` in try/finally with `model.finalize_lib()`
**Example**:
```python
def test_material_properties():
m = openmc.Material()
m.add_nuclide('U235', 1.0)
assert 'U235' in m.nuclides
with pytest.raises(TypeError):
m.add_nuclide('H1', '1.0') # Invalid type
```
Unit tests should be fast. For tests requiring simulation output, use regression tests instead.
### Python Regression Tests
Regression tests compare OpenMC output against reference data. **Prefer using existing models from `openmc.examples` or those found in tests/unit_tests/conftest.py** (like `pwr_pin_cell()`, `pwr_assembly()`, `slab_mg()`) rather than building from scratch.
**Test Harness Types** (in `tests/testing_harness.py`):
- **PyAPITestHarness**: Standard harness for Python API tests. Compares `inputs_true.dat` (XML hash) and `results_true.dat` (statepoint k-eff and tally values). Requires `model.xml` generation.
- **HashedPyAPITestHarness**: Like PyAPITestHarness but hashes the results for compact comparison
- **TolerantPyAPITestHarness**: For tests with floating-point non-associativity (e.g., random ray solver with single precision). Uses relative tolerance comparisons.
- **WeightWindowPyAPITestHarness**: Compares weight window bounds from `weight_windows.h5`
- **CollisionTrackTestHarness**: Compares collision track data from `collision_track.h5` against `collision_track_true.h5`
- **TestHarness**: Base harness for XML-based tests (no Python model building)
- **PlotTestHarness**: Compares plot output files (PNG or voxel HDF5)
- **CMFDTestHarness**: Specialized for CMFD acceleration tests
- **ParticleRestartTestHarness**: Tests particle restart functionality
Almost all cases use either `PyAPITestHarness` or `HashedPyAPITestHarness`
**Example Test**:
```python
from openmc.examples import pwr_pin_cell
from tests.testing_harness import PyAPITestHarness
def test_my_feature():
model = pwr_pin_cell()
model.settings.particles = 1000 # Modify to exercise feature
harness = PyAPITestHarness('statepoint.10.h5', model)
harness.main()
```
**Workflow**: Create `test.py` and `__init__.py` in `tests/regression_tests/my_test/`, run `pytest --update` to generate reference files (`inputs_true.dat`, `results_true.dat`, etc.), then verify with `pytest` without `--update`. Test results should be generated with `-DOPENMC_ENABLE_STRICT_FP=on` to ensure reproducibility across platforms and optimization levels.
**Critical**: When modifying OpenMC code, regenerate affected test references with `pytest --update` and commit updated reference files.
### Test Configuration
`pytest.ini` sets: `python_files = test*.py`, `python_classes = NoThanks` (disables class-based test collection).
### Testing Options
For builds of OpenMC with MPI enabled, the `--mpi` flag should be passed to the test suite to ensure that appropriate tests are executed using two MPI processes.
The entire test suite can be executed with OpenMC running in event-based mode (instead of the default history-based mode) by providing the `--event` flag to the `pytest` command.
## Cross-Language Boundaries
The C API (defined in `include/openmc/capi.h`) exposes C++ functionality to Python via ctypes bindings in `openmc/lib/`. Example:
```cpp
// C++ API in capi.h
extern "C" int openmc_run();
// Python binding in openmc/lib/core.py
_dll.openmc_run.restype = c_int
def run():
_dll.openmc_run()
```
When modifying C++ public APIs, update corresponding ctypes signatures in `openmc/lib/*.py`.
## Code Style & Conventions
### C++ Style (enforced by .clang-format)
OpenMC generally tries to follow C++ core guidelines where possible
(https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines) and follow
modern C++ practices (e.g. RAII) whenever possible.
- **Naming**:
- Classes: `CamelCase` (e.g., `HexLattice`)
- Functions/methods: `snake_case` (e.g., `get_indices`)
- Variables: `snake_case` with trailing underscore for class members (e.g., `n_particles_`, `energy_`)
- Constants: `UPPER_SNAKE_CASE` (e.g., `SQRT_PI`)
- **Namespaces**: All code in `openmc::` namespace, global state in sub-namespaces
- **Include order**: Related header first, then C/C++ stdlib, third-party libs, local headers
- **Comments**: C++-style (`//`) only, never C-style (`/* */`)
- **Standard**: C++17 features allowed
- **Formatting**: Run `clang-format` (version 18) before committing; install via `tools/dev/install-commit-hooks.sh`
### Python Style
- **PEP8** compliant
- **Docstrings**: numpydoc format for all public functions/methods
- **Type hints**: Use sparingly, primarily for complex signatures
- **Path handling**: Use `pathlib.Path` for filesystem operations, accept `str | os.PathLike` in function arguments
- **Dependencies**: Core dependencies only (numpy, scipy, h5py, pandas, matplotlib, lxml, ipython, uncertainties, endf). Other packages must be optional
- **Python version**: Minimum 3.11 (as of Nov 2025)
### ID Management Pattern (Python)
When creating geometry objects, IDs can be auto-assigned or explicit:
```python
# Auto-assigned ID
cell = openmc.Cell() # Gets next available ID
# Explicit ID
cell = openmc.Cell(id=10) # Warning if ID already used
# Reset all IDs (useful in test fixtures)
openmc.reset_auto_ids()
```
### Input Validation Pattern (Python)
All setters use checkvalue functions:
```python
import openmc.checkvalue as cv
@property
def temperature(self):
return self._temperature
@temperature.setter
def temperature(self, temp):
cv.check_type('temperature', temp, Real)
cv.check_greater_than('temperature', temp, 0.0)
self._temperature = temp
```
### Working with HDF5 Files
C++ uses custom HDF5 wrappers in `src/hdf5_interface.cpp`. Python uses h5py directly. Statepoint format version is `VERSION_STATEPOINT` in `include/openmc/constants.h`.
### Conditional Compilation
Check for optional features:
```cpp
#ifdef OPENMC_MPI
// MPI-specific code
#endif
#ifdef OPENMC_DAGMC
// DAGMC-specific code
#endif
```
## Documentation
- **User docs**: Sphinx documentation in `docs/source/` hosted at https://docs.openmc.org
- **C++ docs**: Doxygen-style comments with `\brief`, `\param` tags
- **Python docs**: numpydoc format docstrings
## Common Pitfalls
1. **Forgetting nuclear data**: Tests fail without `OPENMC_CROSS_SECTIONS` environment variable
2. **ID conflicts**: Python objects with duplicate IDs trigger `IDWarning`, use `reset_auto_ids()` between tests
3. **MPI builds**: Code must work with and without MPI; use `#ifdef OPENMC_MPI` guards
4. **Path handling**: Use `pathlib.Path` in new Python code, not `os.path`
5. **Clang-format version**: CI uses version 18; other versions may produce different formatting

View file

@ -1,9 +1,43 @@
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: OpenMC
authors:
- family-names: Romano
given-names: Paul K.
orcid: "https://orcid.org/0000-0002-1147-045X"
- family-names: Shriwise
given-names: Patrick C.
orcid: "https://orcid.org/0000-0002-3979-7665"
- family-names: Shimwell
given-names: Jonathan
orcid: "https://orcid.org/0000-0001-6909-0946"
- family-names: Harper
given-names: Sterling
- family-names: Boyd
given-names: Will
- family-names: Nelson
given-names: Adam G.
orcid: "https://orcid.org/0000-0002-3614-0676"
- family-names: Tramm
given-names: John R.
orcid: "https://orcid.org/0000-0002-5397-4402"
- family-names: Ridley
given-names: Gavin
orcid: "https://orcid.org/0000-0003-1635-8042"
- family-names: Johnson
given-names: Andrew
orcid: "https://orcid.org/0000-0003-2125-8775"
- family-names: Peterson
given-names: Ethan E.
orcid: "https://orcid.org/0000-0002-5694-7194"
- family-names: Herman
given-names: Bryan R.
preferred-citation:
authors:
- family-names: Romano
given-names: Paul K.
orcid: "https://orcid.org/0000-0002-1147-045X"
- final-names: Horelik
- family-names: Horelik
given-names: Nicholas E.
- family-names: Herman
given-names: Bryan R.

14
CLAUDE.md Normal file
View file

@ -0,0 +1,14 @@
## OpenMC Codebase Tools
Read the FULL `AGENTS.md` in this directory before starting work. It contains
project context, coding conventions, and documentation of the RAG search tools
registered in `.mcp.json`.
### Claude Code-specific: first-call behavior
The first `openmc_rag_search` call of each session returns an index status
message instead of search results. When this happens, you MUST use the
`AskUserQuestion` tool to present the rebuild/use-existing choice to the user.
Do not ask conversationally — always use the widget. Do not skip this step even
if the index looks current — the user may have uncommitted changes that warrant
a rebuild.

View file

@ -20,6 +20,11 @@ set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
# Generate compile_commands.json for clangd and other tools
if("${CMAKE_EXPORT_COMPILE_COMMANDS}" STREQUAL "")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
endif()
# Enable correct usage of CXX_EXTENSIONS
if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.22)
cmake_policy(SET CMP0128 NEW)
@ -38,6 +43,7 @@ option(OPENMC_USE_LIBMESH "Enable support for libMesh unstructured mesh tall
option(OPENMC_USE_MPI "Enable MPI" OFF)
option(OPENMC_USE_UWUW "Enable UWUW" OFF)
option(OPENMC_FORCE_VENDORED_LIBS "Explicitly use submodules defined in 'vendor'" OFF)
option(OPENMC_ENABLE_STRICT_FP "Enable strict FP flags to improve test portability" OFF)
message(STATUS "OPENMC_USE_OPENMP ${OPENMC_USE_OPENMP}")
message(STATUS "OPENMC_BUILD_TESTS ${OPENMC_BUILD_TESTS}")
@ -48,6 +54,7 @@ message(STATUS "OPENMC_USE_LIBMESH ${OPENMC_USE_LIBMESH}")
message(STATUS "OPENMC_USE_MPI ${OPENMC_USE_MPI}")
message(STATUS "OPENMC_USE_UWUW ${OPENMC_USE_UWUW}")
message(STATUS "OPENMC_FORCE_VENDORED_LIBS ${OPENMC_FORCE_VENDORED_LIBS}")
message(STATUS "OPENMC_ENABLE_STRICT_FP ${OPENMC_ENABLE_STRICT_FP}")
# Warnings for deprecated options
foreach(OLD_OPT IN ITEMS "openmp" "profile" "coverage" "dagmc" "libmesh")
@ -89,6 +96,19 @@ if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE RelWithDebInfo CACHE STRING "Choose the type of build" FORCE)
endif()
#===============================================================================
# When STRICT_FP is enabled, remove NDEBUG from RelWithDebInfo flags so that
# assert() remains active. CMake normally adds -DNDEBUG for both Release and
# RelWithDebInfo, which disables C/C++ assert() statements.
#===============================================================================
if(OPENMC_ENABLE_STRICT_FP)
foreach(FLAG_VAR CMAKE_CXX_FLAGS_RELWITHDEBINFO CMAKE_C_FLAGS_RELWITHDEBINFO)
string(REPLACE "-DNDEBUG" "" ${FLAG_VAR} "${${FLAG_VAR}}")
string(REPLACE "/DNDEBUG" "" ${FLAG_VAR} "${${FLAG_VAR}}")
endforeach()
endif()
#===============================================================================
# OpenMP for shared-memory parallelism (and GPU support some day!)
#===============================================================================
@ -193,6 +213,26 @@ endif()
# Set compile/link flags based on which compiler is being used
#===============================================================================
# When OPENMC_ENABLE_STRICT_FP is enabled, disable compiler optimizations that change
# floating-point results relative to -O0, improving cross-platform and
# cross-optimization-level reproducibility for regression testing:
# -ffp-contract=off Prevents FMA contraction (fused multiply-add changes rounding)
# -fno-builtin Prevents replacing math function calls (pow, exp, log, etc.)
# with builtin versions that may differ from libm
# By default (OFF), the compiler is free to use all optimizations for best
# performance.
if(OPENMC_ENABLE_STRICT_FP)
include(CheckCXXCompilerFlag)
check_cxx_compiler_flag(-ffp-contract=off SUPPORTS_FP_CONTRACT_OFF)
if(SUPPORTS_FP_CONTRACT_OFF)
list(APPEND cxxflags -ffp-contract=off)
endif()
check_cxx_compiler_flag(-fno-builtin SUPPORTS_NO_BUILTIN)
if(SUPPORTS_NO_BUILTIN)
list(APPEND cxxflags -fno-builtin)
endif()
endif()
# Skip for Visual Studio which has its own configurations through GUI
if(NOT MSVC)
@ -266,23 +306,6 @@ else()
endif()
endif()
#===============================================================================
# xtensor header-only library
#===============================================================================
if(OPENMC_FORCE_VENDORED_LIBS)
add_subdirectory(vendor/xtl)
set(xtl_DIR ${CMAKE_CURRENT_BINARY_DIR}/vendor/xtl)
add_subdirectory(vendor/xtensor)
else()
find_package_write_status(xtensor)
if (NOT xtensor_FOUND)
add_subdirectory(vendor/xtl)
set(xtl_DIR ${CMAKE_CURRENT_BINARY_DIR}/vendor/xtl)
add_subdirectory(vendor/xtensor)
endif()
endif()
#===============================================================================
# Catch2 library
#===============================================================================
@ -332,6 +355,7 @@ endif()
#===============================================================================
list(APPEND libopenmc_SOURCES
src/atomic_mass.cpp
src/bank.cpp
src/boundary_condition.cpp
src/bremsstrahlung.cpp
@ -372,6 +396,7 @@ list(APPEND libopenmc_SOURCES
src/particle.cpp
src/particle_data.cpp
src/particle_restart.cpp
src/particle_type.cpp
src/photon.cpp
src/physics.cpp
src/physics_common.cpp
@ -387,6 +412,7 @@ list(APPEND libopenmc_SOURCES
src/random_ray/linear_source_domain.cpp
src/random_ray/moment_matrix.cpp
src/random_ray/source_region.cpp
src/ray.cpp
src/reaction.cpp
src/reaction_product.cpp
src/scattdata.cpp
@ -425,7 +451,9 @@ list(APPEND libopenmc_SOURCES
src/tallies/filter_musurface.cpp
src/tallies/filter_parent_nuclide.cpp
src/tallies/filter_particle.cpp
src/tallies/filter_particle_production.cpp
src/tallies/filter_polar.cpp
src/tallies/filter_reaction.cpp
src/tallies/filter_sph_harm.cpp
src/tallies/filter_sptl_legendre.cpp
src/tallies/filter_surface.cpp
@ -495,7 +523,7 @@ endif()
# target_link_libraries treats any arguments starting with - but not -l as
# linker flags. Thus, we can pass both linker flags and libraries together.
target_link_libraries(libopenmc ${ldflags} ${HDF5_LIBRARIES} ${HDF5_HL_LIBRARIES}
xtensor fmt::fmt ${CMAKE_DL_LIBS})
fmt::fmt ${CMAKE_DL_LIBS})
if(TARGET pugixml::pugixml)
target_link_libraries(libopenmc pugixml::pugixml)
@ -504,7 +532,7 @@ else()
endif()
if(OPENMC_USE_DAGMC)
target_compile_definitions(libopenmc PRIVATE OPENMC_DAGMC_ENABLED)
target_compile_definitions(libopenmc PUBLIC OPENMC_DAGMC_ENABLED)
target_link_libraries(libopenmc dagmc-shared)
if(OPENMC_USE_UWUW)
@ -552,6 +580,9 @@ endif()
if (OPENMC_ENABLE_COVERAGE)
target_compile_definitions(libopenmc PRIVATE COVERAGEBUILD)
endif()
if (OPENMC_ENABLE_STRICT_FP)
target_compile_definitions(libopenmc PRIVATE OPENMC_ENABLE_STRICT_FP)
endif()
#===============================================================================
# openmc executable
@ -580,9 +611,7 @@ add_custom_command(TARGET libopenmc POST_BUILD
#===============================================================================
# Install executable, scripts, manpage, license
#===============================================================================
configure_file(cmake/OpenMCConfig.cmake.in "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake" @ONLY)
configure_file(cmake/OpenMCConfigVersion.cmake.in "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake" @ONLY)
include(CMakePackageConfigHelpers)
set(INSTALL_CONFIGDIR ${CMAKE_INSTALL_LIBDIR}/cmake/OpenMC)
install(TARGETS openmc libopenmc
@ -596,10 +625,24 @@ install(EXPORT openmc-targets
NAMESPACE OpenMC::
DESTINATION ${INSTALL_CONFIGDIR})
configure_package_config_file(
"cmake/OpenMCConfig.cmake.in"
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
INSTALL_DESTINATION ${INSTALL_CONFIGDIR}
)
write_basic_package_version_file(
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
VERSION ${OPENMC_VERSION}
COMPATIBILITY AnyNewerVersion
)
install(FILES
"${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
"${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
DESTINATION ${INSTALL_CONFIGDIR})
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
DESTINATION "${INSTALL_CONFIGDIR}"
)
install(FILES man/man1/openmc.1 DESTINATION ${CMAKE_INSTALL_MANDIR}/man1)
install(FILES LICENSE DESTINATION "${CMAKE_INSTALL_DOCDIR}" RENAME copyright)
install(DIRECTORY include/ DESTINATION ${CMAKE_INSTALL_INCLUDEDIR})

View file

@ -33,11 +33,6 @@ ARG build_libmesh
# Set default value of HOME to /root
ENV HOME=/root
# Embree variables
ENV EMBREE_TAG='v4.3.1'
ENV EMBREE_REPO='https://github.com/embree/embree'
ENV EMBREE_INSTALL_DIR=$HOME/EMBREE/
# MOAB variables
ENV MOAB_TAG='5.5.1'
ENV MOAB_REPO='https://bitbucket.org/fathomteam/moab/'
@ -58,10 +53,11 @@ ENV LIBMESH_REPO='https://github.com/libMesh/libmesh'
ENV LIBMESH_INSTALL_DIR=$HOME/LIBMESH
# NJOY variables
ENV NJOY_TAG='2016.78'
ENV NJOY_REPO='https://github.com/njoy/NJOY2016'
# Setup environment variables for Docker image
ENV LD_LIBRARY_PATH=${DAGMC_INSTALL_DIR}/lib:$LD_LIBRARY_PATH \
ENV LD_LIBRARY_PATH=${DAGMC_INSTALL_DIR}/lib:${LD_LIBRARY_PATH:-} \
OPENMC_ENDF_DATA=/root/endf-b-vii.1 \
DEBIAN_FRONTEND=noninteractive
@ -71,7 +67,7 @@ RUN apt-get update -y && \
apt-get install -y \
python3-pip python-is-python3 wget git build-essential cmake \
mpich libmpich-dev libhdf5-serial-dev libhdf5-mpich-dev \
libpng-dev python3-venv && \
libpng-dev libpugixml-dev libfmt-dev catch2 python3-venv && \
apt-get autoremove
# create virtual enviroment to avoid externally managed environment error
@ -83,7 +79,7 @@ RUN pip install --upgrade pip
# Clone and install NJOY2016
RUN cd $HOME \
&& git clone --single-branch --depth 1 ${NJOY_REPO} \
&& git clone --single-branch -b ${NJOY_TAG} --depth 1 ${NJOY_REPO} \
&& cd NJOY2016 \
&& mkdir build \
&& cd build \
@ -94,22 +90,12 @@ RUN cd $HOME \
RUN if [ "$build_dagmc" = "on" ]; then \
# Install addition packages required for DAGMC
apt-get -y install libeigen3-dev libnetcdf-dev libtbb-dev libglfw3-dev \
apt-get -y install \
libeigen3-dev libnetcdf-dev libtbb-dev libglfw3-dev libembree-dev \
&& pip install --upgrade numpy \
&& pip install --no-cache-dir setuptools cython \
# Clone and install EMBREE
&& mkdir -p $HOME/EMBREE && cd $HOME/EMBREE \
&& git clone --single-branch -b ${EMBREE_TAG} --depth 1 ${EMBREE_REPO} \
&& mkdir build && cd build \
&& cmake ../embree \
-DCMAKE_INSTALL_PREFIX=${EMBREE_INSTALL_DIR} \
-DEMBREE_MAX_ISA=NONE \
-DEMBREE_ISA_SSE42=ON \
-DEMBREE_ISPC_SUPPORT=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${EMBREE_INSTALL_DIR}/build ${EMBREE_INSTALL_DIR}/embree ; \
# Clone and install MOAB
mkdir -p $HOME/MOAB && cd $HOME/MOAB \
&& mkdir -p $HOME/MOAB && cd $HOME/MOAB \
&& git clone --single-branch -b ${MOAB_TAG} --depth 1 ${MOAB_REPO} \
&& mkdir build && cd build \
&& cmake ../moab -DCMAKE_BUILD_TYPE=Release \
@ -118,6 +104,7 @@ RUN if [ "$build_dagmc" = "on" ]; then \
-DBUILD_SHARED_LIBS=OFF \
-DENABLE_FORTRAN=OFF \
-DENABLE_BLASLAPACK=OFF \
-DENABLE_TESTING=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& cmake ../moab \
-DENABLE_PYMOAB=ON \
@ -133,7 +120,7 @@ RUN if [ "$build_dagmc" = "on" ]; then \
&& mkdir build && cd build \
&& cmake ../double-down -DCMAKE_INSTALL_PREFIX=${DD_INSTALL_DIR} \
-DMOAB_DIR=/usr/local \
-DEMBREE_DIR=${EMBREE_INSTALL_DIR} \
-DEMBREE_DIR=/usr \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${DD_INSTALL_DIR}/build ${DD_INSTALL_DIR}/double-down ; \
# Clone and install DAGMC
@ -147,6 +134,7 @@ RUN if [ "$build_dagmc" = "on" ]; then \
-DDOUBLE_DOWN_DIR=${DD_INSTALL_DIR} \
-DCMAKE_PREFIX_PATH=${DD_INSTALL_DIR}/lib \
-DBUILD_STATIC_LIBS=OFF \
-DBUILD_TESTS=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${DAGMC_INSTALL_DIR}/DAGMC ${DAGMC_INSTALL_DIR}/build ; \
fi

View file

@ -1,4 +1,4 @@
Copyright (c) 2011-2025 Massachusetts Institute of Technology, UChicago Argonne
Copyright (c) 2011-2026 Massachusetts Institute of Technology, UChicago Argonne
LLC, and OpenMC contributors
Permission is hereby granted, free of charge, to any person obtaining a copy of

View file

@ -1,14 +1,18 @@
get_filename_component(OpenMC_CMAKE_DIR "${CMAKE_CURRENT_LIST_FILE}" DIRECTORY)
@PACKAGE_INIT@
# Compute the install prefix from this file's location
get_filename_component(_OPENMC_PREFIX "${OpenMC_CMAKE_DIR}/../../.." ABSOLUTE)
include("${CMAKE_CURRENT_LIST_DIR}/OpenMCConfigVersion.cmake")
include(CMakeFindDependencyMacro)
# Explicitly calculate prefix if it was not generated above
if(NOT DEFINED PACKAGE_PREFIX_DIR)
get_filename_component(PACKAGE_PREFIX_DIR "${CMAKE_CURRENT_LIST_DIR}/../../.." ABSOLUTE)
endif()
find_dependency(fmt CONFIG REQUIRED HINTS ${PACKAGE_PREFIX_DIR})
find_dependency(pugixml CONFIG REQUIRED HINTS ${PACKAGE_PREFIX_DIR})
find_package(fmt CONFIG REQUIRED HINTS ${_OPENMC_PREFIX})
find_package(pugixml CONFIG REQUIRED HINTS ${_OPENMC_PREFIX})
find_package(xtl CONFIG REQUIRED HINTS ${_OPENMC_PREFIX})
find_package(xtensor CONFIG REQUIRED HINTS ${_OPENMC_PREFIX})
if(@OPENMC_USE_DAGMC@)
find_package(DAGMC REQUIRED HINTS @DAGMC_DIR@)
find_dependency(DAGMC REQUIRED HINTS @DAGMC_DIR@)
endif()
if(@OPENMC_USE_LIBMESH@)
@ -18,20 +22,24 @@ if(@OPENMC_USE_LIBMESH@)
pkg_check_modules(LIBMESH REQUIRED @LIBMESH_PC_FILE@>=1.7.0 IMPORTED_TARGET)
endif()
find_package(PNG)
if(NOT TARGET OpenMC::libopenmc)
include("${OpenMC_CMAKE_DIR}/OpenMCTargets.cmake")
if("@PNG_FOUND@")
find_dependency(PNG)
endif()
if(@OPENMC_USE_MPI@)
find_package(MPI REQUIRED)
find_dependency(MPI REQUIRED)
endif()
if(@OPENMC_USE_OPENMP@)
find_package(OpenMP REQUIRED)
find_dependency(OpenMP REQUIRED)
endif()
if(@OPENMC_USE_UWUW@ AND NOT ${DAGMC_BUILD_UWUW})
message(FATAL_ERROR "UWUW is enabled in OpenMC but the DAGMC installation discovered was not configured with UWUW.")
endif()
include("${CMAKE_CURRENT_LIST_DIR}/OpenMCTargets.cmake")
if(NOT OpenMC_FIND_QUIETLY)
message(STATUS "Found OpenMC: ${PACKAGE_VERSION} (found in ${PACKAGE_PREFIX_DIR})")
endif()

View file

@ -1,11 +0,0 @@
set(PACKAGE_VERSION "@OPENMC_VERSION@")
# Check whether the requested PACKAGE_FIND_VERSION is compatible
if("${PACKAGE_VERSION}" VERSION_LESS "${PACKAGE_FIND_VERSION}")
set(PACKAGE_VERSION_COMPATIBLE FALSE)
else()
set(PACKAGE_VERSION_COMPATIBLE TRUE)
if ("${PACKAGE_VERSION}" VERSION_EQUAL "${PACKAGE_FIND_VERSION}")
set(PACKAGE_VERSION_EXACT TRUE)
endif()
endif()

View file

@ -45,6 +45,7 @@ help:
clean:
-rm -rf $(BUILDDIR)/*
-rm -rf source/pythonapi/generated/
-rm -rf doxygen/xml
html:
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html

13
docs/doxygen/Doxyfile Normal file
View file

@ -0,0 +1,13 @@
# Doxyfile 1.9.1
# This file describes the settings to be used by the documentation system
# doxygen (www.doxygen.org) for a project.
# Difference with default Doxyfile 1.9.1
PROJECT_NAME = OpenMC
QUIET = YES
WARN_IF_UNDOCUMENTED = NO
INPUT = ../../include/openmc/capi.h
GENERATE_HTML = NO
GENERATE_LATEX = NO
GENERATE_XML = YES

View file

@ -46,43 +46,20 @@ Type Definitions
Functions
---------
.. c:function:: int openmc_calculate_volumes()
..
Once documentation is complete in capi.h, use:
.. doxygenfile:: capi.h
to populate this documentation without using
.. doxygenfunction::
for every function.
Run a stochastic volume calculation
.. doxygenfunction:: openmc_calculate_volumes
:return: Return status (negative if an error occurred)
:rtype: int
.. doxygenfunction:: openmc_cell_get_fill
.. c:function:: int openmc_cell_get_fill(int32_t index, int* type, int32_t** indices, int32_t* n)
.. doxygenfunction:: openmc_cell_get_id
Get the fill for a cell
:param int32_t index: Index in the cells array
:param int* type: Type of the fill
:param int32_t** indices: Array of material indices for cell
:param int32_t* n: Length of indices array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_cell_get_id(int32_t index, int32_t* id)
Get the ID of a cell
:param int32_t index: Index in the cells array
:param int32_t* id: ID of the cell
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_cell_get_temperature(int32_t index, const int32_t* instance, double* T)
Get the temperature of a cell
:param int32_t index: Index in the cells array
:param int32_t* instance: Which instance of the cell. If a null pointer is passed, the temperature
of the first instance is returned.
:param double* T: temperature of the cell
:return: Return status (negative if an error occurred)
:rtype: int
.. doxygenfunction:: openmc_cell_get_temperature
.. c:function:: int openmc_cell_get_density(int32_t index, const int32_t* instance, double* density)
@ -580,6 +557,279 @@ Functions
:return: Return status (negative if an error occurs)
:rtype: int
.. c:function:: int openmc_get_plot_index(int32_t id, int32_t* index)
Get the index in the plots array for a plot with a given ID.
:param int32_t id: Plot ID
:param int32_t* index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_plot_get_id(int32_t index, int32_t* id)
Get the ID of a plot.
:param int32_t index: Index in the plots array
:param int32_t* id: Plot ID
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_plot_set_id(int32_t index, int32_t id)
Set the ID of a plot.
:param int32_t index: Index in the plots array
:param int32_t id: Plot ID
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: size_t openmc_plots_size()
Number of plots currently allocated.
:return: Number of plots in the plots array
:rtype: size_t
.. c:function:: int openmc_solidraytrace_plot_create(int32_t* index)
Create a new solid raytrace plot.
:param int32_t* index: Index of the newly created plot
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_pixels(int32_t index, int32_t* width, int32_t* height)
Get output pixel dimensions for a solid raytrace plot.
:param int32_t index: Index in the plots array
:param int32_t* width: Image width in pixels
:param int32_t* height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_pixels(int32_t index, int32_t width, int32_t height)
Set output pixel dimensions for a solid raytrace plot.
:param int32_t index: Index in the plots array
:param int32_t width: Image width in pixels
:param int32_t height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_color_by(int32_t index, int32_t* color_by)
Get the domain type used for coloring (0=materials, 1=cells).
:param int32_t index: Index in the plots array
:param int32_t* color_by: Coloring mode
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_color_by(int32_t index, int32_t color_by)
Set the domain type used for coloring (0=materials, 1=cells).
:param int32_t index: Index in the plots array
:param int32_t color_by: Coloring mode
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_default_colors(int32_t index)
Set default random colors for the current ``color_by`` mode.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_all_opaque(int32_t index)
Mark all domains in the current ``color_by`` mode as opaque.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_opaque(int32_t index, int32_t id, bool visible)
Set whether a specific domain ID is opaque (visible) in the rendered image.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param bool visible: Whether the domain is opaque
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_color(int32_t index, int32_t id, uint8_t r, uint8_t g, uint8_t b)
Set RGB color for a specific domain ID.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param uint8_t r: Red channel
:param uint8_t g: Green channel
:param uint8_t b: Blue channel
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_color(int32_t index, int32_t id, uint8_t* r, uint8_t* g, uint8_t* b)
Get RGB color for a specific domain ID.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param uint8_t* r: Red channel
:param uint8_t* g: Green channel
:param uint8_t* b: Blue channel
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_camera_position(int32_t index, double* x, double* y, double* z)
Get camera position.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_camera_position(int32_t index, double x, double y, double z)
Set camera position.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_look_at(int32_t index, double* x, double* y, double* z)
Get camera target point.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_look_at(int32_t index, double x, double y, double z)
Set camera target point.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_up(int32_t index, double* x, double* y, double* z)
Get the camera up vector.
:param int32_t index: Index in the plots array
:param double* x: X component
:param double* y: Y component
:param double* z: Z component
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_up(int32_t index, double x, double y, double z)
Set the camera up vector.
:param int32_t index: Index in the plots array
:param double x: X component
:param double y: Y component
:param double z: Z component
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_light_position(int32_t index, double* x, double* y, double* z)
Get light source position.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_light_position(int32_t index, double x, double y, double z)
Set light source position.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_fov(int32_t index, double* fov)
Get horizontal field of view in degrees.
:param int32_t index: Index in the plots array
:param double* fov: Field of view in degrees
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_fov(int32_t index, double fov)
Set horizontal field of view in degrees.
:param int32_t index: Index in the plots array
:param double fov: Field of view in degrees
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_diffuse_fraction(int32_t index, double* diffuse_fraction)
Get diffuse-light fraction.
:param int32_t index: Index in the plots array
:param double* diffuse_fraction: Diffuse fraction in [0, 1]
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_diffuse_fraction(int32_t index, double diffuse_fraction)
Set diffuse-light fraction.
:param int32_t index: Index in the plots array
:param double diffuse_fraction: Diffuse fraction in [0, 1]
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_update_view(int32_t index)
Recompute internal camera/view transforms after camera changes.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_create_image(int32_t index, uint8_t* data_out, int32_t width, int32_t height)
Render the plot to an RGB image buffer.
:param int32_t index: Index in the plots array
:param uint8_t* data_out: Output buffer of shape ``height*width*3``
:param int32_t width: Image width in pixels
:param int32_t height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_reset()
Resets all tally scores
@ -601,6 +851,10 @@ Functions
:return: Return status (negative if an error occurs)
:rtype: int
.. c:function:: void openmc_run_random_ray()
Run a random ray simulation
.. c:function:: int openmc_set_n_batches(int32_t n_batches, bool set_max_batches, bool add_statepoint_batch)
Set number of batches and number of max batches

View file

@ -11,7 +11,10 @@
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys, os
import os
from pathlib import Path
import subprocess
import sys
# Determine if we're on Read the Docs server
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
@ -37,6 +40,7 @@ sys.path.insert(0, os.path.abspath('../..'))
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = [
'breathe',
'sphinx.ext.autodoc',
'sphinx.ext.napoleon',
'sphinx.ext.autosummary',
@ -47,6 +51,8 @@ extensions = [
]
if not on_rtd:
extensions.append('sphinxcontrib.rsvgconverter')
doxygen_dir = Path(__file__).parents[1] / 'doxygen'
subprocess.run(['doxygen'], cwd=doxygen_dir, check=True)
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
@ -62,7 +68,7 @@ master_doc = 'index'
# General information about the project.
project = 'OpenMC'
copyright = '2011-2025, Massachusetts Institute of Technology, UChicago Argonne LLC, and OpenMC contributors'
copyright = '2011-2026, Massachusetts Institute of Technology, UChicago Argonne LLC, and OpenMC contributors'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
@ -117,6 +123,11 @@ pygments_style = 'tango'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options breathe + doxygen -------------------------------------------------
breathe_projects = {"OpenMC": "../doxygen/xml"}
breathe_default_project = "OpenMC"
breathe_domain_by_file_pattern = {"*capi.h": "c"}
# -- Options for HTML output ---------------------------------------------------

View file

@ -0,0 +1,104 @@
.. _devguide_agentic_tools:
===========================
Agentic Development Tools
===========================
OpenMC ships a set of tools designed for AI coding agents (such as
`Claude Code`_) that agents can use to navigate and understand the codebase.
.. _Claude Code: https://claude.ai/code
Motivation
----------
Agentic tools like Claude Code are skilled at using grep to navigate and
understand large code bases. However, grep can only find exact text matches —
it cannot discover code that is *conceptually* related but uses different
naming. Without a "global view" of the codebase that a human developer will
build up over time, the agent is generally blind to any file it hasn't
tokenized fully. While it can grep to see who else calls a function, it
remains blind if other areas might be related but not share identical naming
conventions.
This problem is mitigated somewhat by using a model with a longer context
window. OpenMC has somewhere around ~1 million tokens of C++ and ~1 million
tokens of python. While Claude Code in early 2026 only has a context window
of 200k tokens, beta versions have extended context windows of 1M tokens,
and it's not unreasonable to assume that models may be available in the near
future that greatly exceed these limits.
However, even assuming the entire repository can be fit within a context
window, there are several downsides to doing this.
`Model performance degrades significantly as context size increases`_.
Benchmark results are
greatly improved if the model has less garbage to pick through. Additionally, API usage
is typically billed as tokens in/out per turn. As the context file
grows these costs become much larger. As such, there is still significant
motivation to solving the above problem, so as to ensure only relevant
information is drawn into context so as to maximize model performance and
minimize costs.
Setup
-----
The tools are registered as an `MCP (Model Context Protocol)`_ server in
``.mcp.json`` at the repository root. AI agents that support MCP (such as
Claude Code) discover them automatically on session start. The underlying
Python scripts can also be run directly from the command line.
All tools run entirely locally — no API keys or external service accounts are
required. Python dependencies are installed automatically into an isolated
virtual environment at ``.claude/cache/.venv/`` on first use.
.. _Model performance degrades significantly as context size increases: https://www.anthropic.com/news/claude-opus-4-6
.. _MCP (Model Context Protocol): https://modelcontextprotocol.io
RAG Semantic Search
-------------------
The RAG (Retrieval-Augmented Generation) semantic search addresses this
problem — it finds code by meaning, not just text match, surfacing related code
across subsystems that ``grep`` would miss entirely. Two MCP tools are provided:
- **openmc_rag_search** — Given a natural-language query, returns the most
relevant code chunks with file paths, line numbers, and a preview. Can search
code, documentation, or both. Can also find code related to a given file.
- **openmc_rag_rebuild** — Rebuilds the search index. Should be called after
pulling new code or switching branches.
How it works
^^^^^^^^^^^^
The search pipeline runs entirely on your local CPU:
1. **Chunking.** All C++, Python, and RST files are split into overlapping
fixed-size windows (~1000 characters, 25% overlap). This ensures every line
of code appears in at least one chunk and most lines appear in two.
2. **Embedding.** Each chunk is embedded into a 384-dimensional vector using
the `all-MiniLM-L6-v2`_ sentence-transformer model (22 million parameters).
This model runs on CPU with no GPU required. No API key is needed — the
model weights are downloaded once from Hugging Face and cached locally.
3. **Indexing.** The vectors are stored in a local LanceDB_ database on disk.
Building the full index takes approximately 5 minutes on a machine with
10 CPU cores. The index is stored in ``.claude/cache/rag_index/`` and
persists across sessions.
4. **Searching.** Your query is embedded using the same model, and the closest
chunks are retrieved by vector similarity. Results include the file path,
line range, file type, similarity distance, and a text preview.
.. _all-MiniLM-L6-v2: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
.. _LanceDB: https://lancedb.com
Requirements
^^^^^^^^^^^^
No system dependencies beyond **Python 3.12+** with ``pip``. An internet
connection is required on first use to download the Python packages and
embedding model weights; subsequent runs are fully offline. The Python packages
(``sentence-transformers``, ``lancedb``) and their dependencies (including
PyTorch, ~2GB) are installed automatically into an isolated virtual environment
on first use.

View file

@ -111,7 +111,8 @@ The TC consists of the following individuals:
- `Paul Romano <https://github.com/paulromano>`_
- `Patrick Shriwise <https://github.com/pshriwise>`_
- `Adam Nelson <https://github.com/nelsonag>`_
- `Benoit Forget <https://github.com/bforget>`_
- `Jonathan Shimwell <https://github.com/shimwell>`_
- `John Tramm <https://github.com/jtramm>`_
The Project Lead is Paul Romano.

View file

@ -14,6 +14,11 @@ Python API. That is, from the root directory of the OpenMC repository:
python -m pip install ".[docs]"
The OpenMC documentation also uses Doxygen to automatically generate its
C/C++ API documentation directly from the docstrings available in the source
code. You will need to have a working installation of Doxygen to generate the
documentation locally.
-----------------------------------
Building Documentation as a Webpage
-----------------------------------

View file

@ -14,6 +14,7 @@ other related topics.
contributing
workflow
agentic-tools
styleguide
policies
tests

View file

@ -21,8 +21,8 @@ C++ code in OpenMC must conform to the most recent C++ standard that is fully
supported in the `version of the gcc compiler
<https://gcc.gnu.org/projects/cxx-status.html>`_ that is distributed with the
oldest version of Ubuntu that is still within its `standard support period
<https://ubuntu.com/about/release-cycle>`_. Ubuntu 20.04 LTS will be supported
through April 2025 and is distributed with gcc 9.3.0, which fully supports the
<https://ubuntu.com/about/release-cycle>`_. Ubuntu 22.04 LTS will be supported
through April 2027 and is distributed with gcc 11.4.0, which fully supports the
C++17 standard.
--------------------
@ -31,5 +31,5 @@ CMake Version Policy
Similar to the C++ standard policy, the minimum supported version of CMake
corresponds to whatever version is distributed with the oldest version of Ubuntu
still within its standard support period. Ubuntu 20.04 LTS is distributed with
CMake 3.16.
still within its standard support period. Ubuntu 22.04 LTS is distributed with
CMake 3.22.

View file

@ -30,7 +30,7 @@ whenever a file is saved. For example, `Visual Studio Code
support for running clang-format.
.. note::
OpenMC's CI uses `clang-format` version 15. A different version of `clang-format`
OpenMC's CI uses `clang-format` version 18. A different version of `clang-format`
may produce different line changes and as a result fail the CI test.
Miscellaneous

View file

@ -37,6 +37,9 @@ Prerequisites
- Some tests require `NJOY <https://www.njoy21.io/NJOY2016>`_ to preprocess
cross section data. The test suite assumes that you have an ``njoy``
executable available on your :envvar:`PATH`.
- OpenMC should be compiled with ``-DOPENMC_ENABLE_STRICT_FP=on`` to ensure
reproducible floating-point results across platforms and optimization levels.
Without this flag, regression tests may not match reference values.
Running Tests
-------------
@ -67,9 +70,11 @@ make sure you have satisfied all the prerequisites above. After you have done
that, consider the following:
- When building OpenMC, make sure you run CMake with
``-DCMAKE_BUILD_TYPE=Debug``. Building with a release build will result in
some test failures due to differences in which compiler optimizations are
used.
``-DOPENMC_ENABLE_STRICT_FP=on``. This prevents the compiler from applying
floating-point optimizations (such as replacing math library calls with
builtins or contracting multiply-add into FMA instructions) that can produce
bit-level differences across platforms and optimization levels. Any
``CMAKE_BUILD_TYPE`` can be used.
- Because tallies involve the sum of many floating point numbers, the
non-associativity of floating point numbers can result in different answers
especially when the number of threads is high (different order of operations).

View file

@ -10,7 +10,7 @@ may also be written after each batch when multiple files are requested
(``collision_track.N.h5``) or when the run is performed in parallel. The file
contains the information needed to reconstruct each recorded collision.
The current revision of the collision track file format is 1.0.
The current revision of the collision track file format is 1.2.
**/**
@ -33,13 +33,13 @@ The current revision of the collision track file format is 1.0.
- ``event_mt`` (*int*) -- ENDF MT number identifying the reaction.
- ``delayed_group`` (*int*) -- Delayed neutron group index (non-zero for delayed events).
- ``cell_id`` (*int*) -- ID of the cell in which the collision occurred.
- ``nuclide_id`` (*int*) -- ZA identifier of the nuclide (ZZZAAAM format).
- ``nuclide_id`` (*int*) -- PDG number of the nuclide (100ZZZAAAM).
- ``material_id`` (*int*) -- ID of the material containing the collision site.
- ``universe_id`` (*int*) -- ID of the universe containing the collision site.
- ``n_collision`` (*int*) -- Collision counter for the particle history.
- ``particle`` (*int*) -- Particle type (0=neutron, 1=photon, 2=electron, 3=positron).
- ``parent_id`` (*int64*) -- Unique ID of the parent particle.
- ``progeny_id`` (*int64*) -- Progeny ID of the particle.
- ``particle`` (*int32_t*) -- Particle type (PDG number).
- ``parent_id`` (*int64_t*) -- Unique ID of the parent particle.
- ``progeny_id`` (*int64_t*) -- Progeny ID of the particle.
In an MPI run, OpenMC writes the combined dataset by gathering collision-track
entries from all ranks before flushing them to disk, so the final file appears

View file

@ -4,7 +4,7 @@
Depletion Results File Format
=============================
The current version of the depletion results file format is 1.2.
The current version of the depletion results file format is 1.3.
**/**
@ -29,11 +29,14 @@ The current version of the depletion results file format is 1.2.
- **depletion time** (*double[]*) -- Average process time in [s]
spent depleting a material across all burnable materials and,
if applicable, MPI processes.
- **keff_search_root** (*double[]*) -- Root of the keff search at the
end of the timestep, if applicable.
**/materials/<id>/**
:Attributes: - **index** (*int*) -- Index used in results for this material
- **volume** (*double*) -- Volume of this material in [cm^3]
- **name** (*char[]*) -- Name of this material
**/nuclides/<name>/**

View file

@ -38,11 +38,9 @@ Each ``<surface>`` element can have the following attributes or sub-elements:
:boundary:
The boundary condition for the surface. This can be "transmission",
"vacuum", "reflective", or "periodic". Periodic boundary conditions can
only be applied to x-, y-, and z-planes. Only axis-aligned periodicity is
supported, i.e., x-planes can only be paired with x-planes. Specify which
planes are periodic and the code will automatically identify which planes
are paired together.
"vacuum", "reflective", or "periodic". Specify which planes are
periodic and the code will automatically identify which planes are
paired together.
*Default*: "transmission"
@ -318,9 +316,10 @@ the following attributes or sub-elements:
*Default*: None
:orientation:
The orientation of the hexagonal lattice. The string "x" indicates that two
sides of the lattice are parallel to the x-axis, whereas the string "y"
indicates that two sides are parallel to the y-axis.
The orientation of the hexagonal lattice. The string "x" indicates that each
lattice element has two faces that are perpendicular to the x-axis, whereas
the string "y" indicates that each lattice element has two faces that are
perpendicular to the y-axis.
*Default*: "y"
@ -407,24 +406,55 @@ Each ``<dagmc_universe>`` element can have the following attributes or sub-eleme
*Default*: None
:material_overrides:
This element contains information on material overrides to be applied to the
DAGMC universe. It has the following attributes and sub-elements:
:cell:
Zero or more ``<cell>`` sub-elements may appear to override properties of
individual DAGMC volumes. Each ``<cell>`` element supports the following
attributes and sub-elements:
:cell:
Material override information for a single cell. It contains the following
attributes and sub-elements:
:id:
The integer cell ID in the DAGMC geometry to override. Required.
:id:
The cell ID in the DAGMC geometry for which the material override will
apply.
:name:
An optional string label for the cell.
:materials:
A list of material IDs that will apply to instances of the cell. If the
list contains only one ID, it will replace the original material
assignment of all instances of the DAGMC cell. If the list contains more
than one material, each material ID of the list will be assigned to the
various instances of the DAGMC cell.
*Default*: None
:material:
The material ID to assign to this cell. Use ``void`` for vacuum. Multiple
space-separated IDs may be given to specify a distribmat (distributed
material) assignment. Required.
:temperature:
Temperature(s) in [K] to assign to the cell. Must be greater than or equal
to 0. Multiple space-separated values may be given.
*Default*: None
:density:
Density in [g/cm³] to assign to the cell. Must be greater than 0. Requires a non-void
material fill. Multiple space-separated values may be given.
*Default*: None
:volume:
Volume of the cell in [cm³].
.. note:: DAGMC can compute cell volumes exactly from the triangulated
mesh surfaces. Specifying a manual volume risks inconsistency
with that capability.
*Default*: None
The following standard ``<cell>`` attributes are **not** supported inside
``<dagmc_universe>`` and will raise an error if present: ``region``,
``fill``, ``universe``, ``translation``, ``rotation``.
.. deprecated::
The ``<material_overrides>`` sub-element (containing ``<cell_override>``
children with ``<material_ids>``) is deprecated. A deprecation warning is
emitted and the overrides are converted to the ``<cell>`` format at parse
time. It is an error to specify both ``<material_overrides>`` and
``<cell>`` sub-elements on the same ``<dagmc_universe>``.
*Default*: None

View file

@ -133,6 +133,10 @@ Temperature-dependent data, provided for temperature <TTT>K.
This dataset is optional. This is a 1-D vector if `representation`
is "isotropic", or a 3-D vector if `representation` is "angle"
with dimensions of [polar][azimuthal][groups].
When this data is not available, an approximation using the
group energy boundaries is used. For more information see
the particle speed subsection in the multigroup-data section
of the theory manual.
**/<library name>/<TTT>K/scatter_data/**

View file

@ -4,7 +4,7 @@
Particle Restart File Format
============================
The current version of the particle restart file format is 2.0.
The current version of the particle restart file format is 2.1.
**/**
@ -26,8 +26,7 @@ The current version of the particle restart file format is 2.0.
- **run_mode** (*char[]*) -- Run mode used, either 'fixed source',
'eigenvalue', or 'particle restart'.
- **id** (*int8_t*) -- Unique identifier of the particle.
- **type** (*int*) -- Particle type (0=neutron, 1=photon, 2=electron,
3=positron)
- **type** (*int32_t*) -- Particle type (PDG number)
- **weight** (*double*) -- Weight of the particle.
- **energy** (*double*) -- Energy of the particle in eV for
continuous-energy mode, or the energy group of the particle for

View file

@ -7,6 +7,19 @@ Settings Specification -- settings.xml
All simulation parameters and miscellaneous options are specified in the
settings.xml file.
-------------------------------
``<atomic_relaxation>`` Element
-------------------------------
The ``<atomic_relaxation>`` element determines whether the atomic relaxation
cascade, the X-ray fluorescence photons and Auger electrons emitted when an
inner-shell vacancy is filled, is simulated following photoelectric and
incoherent (Compton) scattering interactions. Disabling this can speed up
photon transport calculations where the detailed secondary particle cascade is
not of interest.
*Default*: true
---------------------
``<batches>`` Element
---------------------
@ -85,6 +98,11 @@ sub-elements:
A list of strings representing the nuclide, to define specific
define specific target nuclide collisions to be banked.
.. note::
Electron and positron collision-track events are not associated with
a specific nuclide. If a ``nuclides`` entry is specified, these events
are omitted.
*Default*: None
:reactions:
@ -277,6 +295,15 @@ ignored for all run modes other than "eigenvalue".
*Default*: 1
------------------------------
``<ifp_n_generation>`` Element
------------------------------
The ``<ifp_n_generation>`` element indicates the number of generations to
consider for the Iterated Fission Probability method.
*Default*: 10
----------------------
``<inactive>`` Element
----------------------
@ -402,7 +429,25 @@ then, OpenMC will only use up to the :math:`P_1` data.
``<max_history_splits>`` Element
--------------------------------
The ``<max_history_splits>`` element indicates the number of times a particle can split during a history.
The ``<max_history_splits>`` element indicates the number of times a particle
can split during a history.
*Default*: 1000
-----------------------------
``<max_secondaries>`` Element
-----------------------------
The ``<max_secondaries>`` element indicates the maximum secondary bank size.
*Default*: 10000
------------------------
``<max_tracks>`` Element
------------------------
The ``<max_tracks>`` element indicates the maximum number of tracks written to a
track file (per MPI process).
*Default*: 1000
@ -515,6 +560,18 @@ generator during generation of colors in plots.
*Default*: 1
.. _properties_file:
-----------------------------
``<properties_file>`` Element
-----------------------------
The ``properties_file`` element has no attributes and contains the path to a
properties HDF5 file to load cell temperatures/densities and material
densities.
*Default*: None
---------------------
``<ptables>`` Element
---------------------
@ -545,7 +602,7 @@ found in the :ref:`random ray user guide <random_ray>`.
*Default*: None
:source:
:ray_source:
Specifies the starting ray distribution, and follows the format for
:ref:`source_element`. It must be uniform in space and angle and cover the
full domain. It does not represent a physical neutron or photon source -- it
@ -553,6 +610,35 @@ found in the :ref:`random ray user guide <random_ray>`.
*Default*: None
:adjoint_source:
Specifies an adjoint fixed source for adjoint transport simulations, and
follows the format for :ref:`source_element`. The distributions which make
up the adjoint source are subject to the same restrictions as forward
fixed sources in Random Ray mode.
*Default*: None
:adjoint:
Specifies whether to perform adjoint transport. The default is 'False',
corresponding to forward transport.
*Default*: None
:volume_estimator:
Specifies choice of volume estimator for the random ray solver. Options
are 'naive', 'simulation_averaged', or 'hybrid'. The default is 'hybrid'.
*Default*: None
:volume_normalized_flux_tallies:
Specifies whether to normalize flux tallies by volume (bool). The
default is 'False'. When enabled, flux tallies will be reported in units
of cm/cm^3. When disabled, flux tallies will be reported in units of cm
(i.e., total distance traveled by neutrons in the spatial tally
region).
*Default*: None
:sample_method:
Specifies the method for sampling the starting ray distribution. This
element can be set to "prng" or "halton".
@ -660,14 +746,16 @@ pseudo-random number generator.
*Default*: 1
--------------------
``<stride>`` Element
--------------------
-----------------------------------
``<shared_secondary_bank>`` Element
-----------------------------------
The ``stride`` element is used to specify how many random numbers are allocated
for each source particle history.
*Default*: 152,917
The ``shared_secondary_bank`` element indicates whether to use a shared
secondary particle bank. When enabled, secondary particles are collected into
a global bank, sorted for reproducibility, and load-balanced across MPI ranks
between generations. If not specified, the shared secondary bank is enabled
automatically for fixed-source simulations with weight windows active, and
disabled otherwise.
.. _source_element:
@ -689,12 +777,15 @@ attributes/sub-elements:
*Default*: 1.0
:type:
Indicator of source type. One of ``independent``, ``file``, ``compiled``, or
``mesh``. The type of the source will be determined by this attribute if it
is present.
Indicator of source type. One of ``independent``, ``file``, ``compiled``,
``mesh``, or ``tokamak``. The type of the source will be determined by this
attribute if it is present.
:particle:
The source particle type, either ``neutron`` or ``photon``.
The source particle type, specified as a PDG number or a string alias (e.g.,
``neutron``/``n``, ``photon``/``gamma``, ``electron``, ``positron``,
``proton``/``p``, ``deuteron``/``d``, ``triton``/``t``, ``alpha``, or GNDS
nuclide names like ``Fe57``).
*Default*: neutron
@ -784,6 +875,7 @@ attributes/sub-elements:
For a "cylindrical" distribution, no parameters are specified. Instead,
the ``r``, ``phi``, ``z``, and ``origin`` elements must be specified.
Optionally, the ``r_dir`` and ``z_dir`` elements could be specified.
For a "spherical" distribution, no parameters are specified. Instead,
the ``r``, ``theta``, ``phi``, and ``origin`` elements must be specified.
@ -815,6 +907,10 @@ attributes/sub-elements:
of a univariate probability distribution (see the description in
:ref:`univariate`).
:r_dir:
For "cylindrical" distributions, this element specifies the direction
of the cylinder r-axis at phi=0. Defaults to (1.0, 0.0, 0.0).
:theta:
For a "spherical" distribution, this element specifies the distribution
of theta-coordinates. The necessary sub-elements/attributes are those of a
@ -827,6 +923,10 @@ attributes/sub-elements:
sub-elements/attributes are those of a univariate probability
distribution (see the description in :ref:`univariate`).
:z_dir:
For "cylindrical" distributions, this element specifies the direction
of the cylinder z-axis. Defaults to (0.0, 0.0, 1.0).
:origin:
For "cylindrical and "spherical" distributions, this element specifies
the coordinates for the origin of the coordinate system.
@ -844,13 +944,18 @@ attributes/sub-elements:
relative source strength of each mesh element or each point in the cloud.
:volume_normalized:
For "mesh" spatial distrubtions, this optional boolean element specifies
For "mesh" spatial distributions, this optional boolean element specifies
whether the vector of relative strengths should be multiplied by the mesh
element volume. This is most common if the strengths represent a source
per unit volume.
*Default*: false
:bias:
For "mesh" and "cloud" spatial distributions, this optional element
specifies floating point values corresponding to alternative probabilities
for each value/component to use for biased sampling.
:angle:
An element specifying the angular distribution of source sites. This element
has the following attributes:
@ -883,6 +988,10 @@ attributes/sub-elements:
are those of a univariate probability distribution (see the description in
:ref:`univariate`).
:bias:
For "isotropic" angular distributions, this optional element specifies a
"mu-phi" angular distribution used for biased sampling.
:energy:
An element specifying the energy distribution of source sites. The necessary
sub-elements/attributes are those of a univariate probability distribution
@ -906,6 +1015,84 @@ attributes/sub-elements:
mesh element and follows the format for :ref:`source_element`. The number of
``<source>`` sub-elements should correspond to the number of mesh elements.
For a source with ``type="tokamak"``, the spatial distribution is described by
a Miller-style flux-surface parameterization and the following sub-elements
are used instead of the ``space`` element:
:major_radius:
The major radius :math:`R_0` of the plasma in [cm].
:minor_radius:
The minor radius :math:`a` of the plasma in [cm]. Must be smaller than
``major_radius``.
:elongation:
The plasma elongation :math:`\kappa` (must be > 0).
:triangularity:
The plasma triangularity :math:`\delta` (must be in [-1, 1]). Negative
values describe negative-triangularity plasmas.
:shafranov_shift:
The Shafranov shift :math:`\Delta` in [cm] (must be >= 0 and less than
``minor_radius``/2).
:r_over_a:
A list of normalized minor-radius grid points :math:`r/a`. Must be strictly
increasing, start at 0, and end at 1.
:emission_density:
A list of neutron emission densities :math:`S(r)` evaluated at each
``r_over_a`` grid point (arbitrary units, must be non-negative). Only the
shape matters, since the profile is normalized internally. Values are
interpolated linearly between grid points and the profile is refined on an
internal grid for radial sampling. Must have the same length as
``r_over_a`` and contain at least one positive value.
:phi_start:
The starting toroidal angle in [rad].
*Default*: 0.0
:phi_extent:
The toroidal angle extent in [rad]. The source is sampled uniformly in
:math:`[\phi_\text{start},\ \phi_\text{start} + \phi_\text{extent}]`.
*Default*: :math:`2\pi`
:n_alpha:
The number of poloidal-angle grid points used to build the sampling CDFs
(must be > 2). Larger values reduce discretization bias; values below 51
produce a warning.
*Default*: 101
:vertical_shift:
A vertical shift of the plasma center in [cm].
*Default*: 0.0
:energy:
For a tokamak source, one or more ``energy`` sub-elements specify the
neutron energy distribution(s). Either a single distribution is given (used
at all radii) or exactly one distribution per ``r_over_a`` grid point is
given, in which case the energy is sampled from one of the two
distributions bracketing the sampled radius, selected stochastically with
probability proportional to the proximity of the radius to each grid point
(stochastic interpolation). Each follows the format of a univariate
probability distribution (see :ref:`univariate`).
:time:
An optional ``time`` sub-element specifying the time distribution of source
particles, following the format of a univariate probability distribution
(see :ref:`univariate`).
*Default*: particles are born at :math:`t=0`
.. note:: Biased sampling can be applied to the spatial and energy distributions
of a source by using the ``<bias>`` sub-element (see
:ref:`univariate` for details on how to specify bias distributions).
:constraints:
This sub-element indicates the presence of constraints on sampled source
sites (see :ref:`usersguide_source_constraints` for details). It may have
@ -952,17 +1139,19 @@ variable and whose sub-elements/attributes are as follows:
:type:
The type of the distribution. Valid options are "uniform", "discrete",
"tabular", "maxwell", "watt", and "mixture". The "uniform" option produces
variates sampled from a uniform distribution over a finite interval. The
"discrete" option produces random variates that can assume a finite number
of values (i.e., a distribution characterized by a probability mass function).
The "tabular" option produces random variates sampled from a tabulated
distribution where the density function is either a histogram or
"tabular", "maxwell", "watt", "mixture", and "decay_spectrum". The "uniform"
option produces variates sampled from a uniform distribution over a finite
interval. The "discrete" option produces random variates that can assume a
finite number of values (i.e., a distribution characterized by a probability
mass function). The "tabular" option produces random variates sampled from a
tabulated distribution where the density function is either a histogram or
linearly-interpolated between tabulated points. The "watt" option produces
random variates is sampled from a Watt fission spectrum (only used for
energies). The "maxwell" option produce variates sampled from a Maxwell
fission spectrum (only used for energies). The "mixture" option produces samples
from univariate sub-distributions with given probabilities.
fission spectrum (only used for energies). The "mixture" option produces
samples from univariate sub-distributions with given probabilities. The
"decay_spectrum" option produces photon energies sampled from decay photon
spectra in a depletion chain (only used for energies).
*Default*: None
@ -980,6 +1169,10 @@ variable and whose sub-elements/attributes are as follows:
:math:`(x,p)` pairs defining the discrete/tabular distribution. All :math:`x`
points are given first followed by corresponding :math:`p` points.
For a "decay_spectrum" distribution, ``parameters`` gives the atom densities
in [atom/b-cm] for the nuclides listed in the ``nuclides`` element, in the
same order.
For a "watt" distribution, ``parameters`` should be given as two real numbers
:math:`a` and :math:`b` that parameterize the distribution :math:`p(x) dx = c
e^{-x/a} \sinh \sqrt{b \, x} dx`.
@ -998,13 +1191,41 @@ variable and whose sub-elements/attributes are as follows:
*Default*: histogram
:pair:
For a "mixture" distribution, this element provides a distribution and its corresponding probability.
For a "mixture" distribution, this element provides a distribution and its
corresponding probability.
:probability:
An attribute or ``pair`` that provides the probability of a univariate distribution within a "mixture" distribution.
An attribute or ``pair`` that provides the probability of a univariate
distribution within a "mixture" distribution.
:dist:
This sub-element of a ``pair`` element provides information on the corresponding univariate distribution.
This sub-element of a ``pair`` element provides information on the
corresponding univariate distribution.
:volume:
For a "decay_spectrum" distribution, this attribute specifies the source
region volume in cm\ :sup:`3`. It is used together with atom densities to
determine the absolute photon emission rate. When a source uses a
"decay_spectrum" energy distribution, the source strength is set from this
emission rate.
:nuclides:
For a "decay_spectrum" distribution, this element specifies a
whitespace-separated list of nuclide names contributing to the decay photon
source. The atom densities for these nuclides are given by the ``parameters``
element in the same order. Nuclides are resolved against the depletion chain,
and nuclides without decay photon spectra do not contribute to the
distribution.
:bias:
This optional element specifies a biased distribution for importance sampling.
For continuous distributions, the ``bias`` element should contain another
univariate distribution with the same support (interval) as the parent
distribution. For discrete distributions, the ``bias`` element should contain
floating point values corresponding to alternative probabilities for each
value/component to be used for biased sampling.
*Default*: None
---------------------------------------
``<source_rejection_fraction>`` Element
@ -1016,23 +1237,6 @@ based on constraints.
*Default*: 0.05
-------------------------
``<state_point>`` Element
-------------------------
The ``<state_point>`` element indicates at what batches a state point file
should be written. A state point file can be used to restart a run or to get
tally results at any batch. The default behavior when using this tag is to
write out the source bank in the state_point file. This behavior can be
customized by using the ``<source_point>`` element. This element has the
following attributes/sub-elements:
:batches:
A list of integers separated by spaces indicating at what batches a state
point file should be written.
*Default*: Last batch only
--------------------------
``<source_point>`` Element
--------------------------
@ -1082,6 +1286,32 @@ attributes/sub-elements:
*Default*: false
-------------------------
``<state_point>`` Element
-------------------------
The ``<state_point>`` element indicates at what batches a state point file
should be written. A state point file can be used to restart a run or to get
tally results at any batch. The default behavior when using this tag is to
write out the source bank in the state_point file. This behavior can be
customized by using the ``<source_point>`` element. This element has the
following attributes/sub-elements:
:batches:
A list of integers separated by spaces indicating at what batches a state
point file should be written.
*Default*: Last batch only
--------------------
``<stride>`` Element
--------------------
The ``stride`` element is used to specify how many random numbers are allocated
for each source particle history.
*Default*: 152,917
------------------------------
``<surf_source_read>`` Element
------------------------------
@ -1169,6 +1399,23 @@ attributes/sub-elements:
are not eligible to store any particles when using ``cell``, ``cellfrom``
or ``cellto`` attributes. It is recommended to use surface IDs instead.
------------------------------------
``<surface_grazing_cutoff>`` Element
------------------------------------
The ``<surface_grazing_cutoff>`` element specifies the surface flux cosine cutoff.
*Default*: 0.001
-----------------------------------
``<surface_grazing_ratio>`` Element
-----------------------------------
The ``<surface_grazing_ratio>`` element specifies the surface flux cosine
substitution ratio.
*Default*: 0.5
------------------------------
``<survival_biasing>`` Element
------------------------------
@ -1352,6 +1599,15 @@ has the following attributes/sub-elements:
for fixed source and small criticality calculations, but is very
optimistic for highly coupled full-core reactor problems.
-------------------------------------
``<uniform_source_sampling>`` Element
-------------------------------------
The ``<uniform_source_sampling>`` element indicates whether to sample among
multiple sources uniformly, applying their strengths as weights to sampled
particles.
*Default*: False
------------------------
``<ufs_mesh>`` Element
@ -1364,6 +1620,16 @@ Agency Monte Carlo Performance Benchmark Problem," Proceedings of *Physor 2012*,
Knoxville, TN (2012). The mesh should cover all possible fissionable materials
in the problem and is specified using a :ref:`mesh_element`.
-------------------------------
``<use_decay_photons>`` Element
-------------------------------
The ``<use_decay_photons>`` element indicates whether to produce decay photons
from neutron reactions instead of prompt photons. This is used in conjunction
with the direct 1-step method for shutdown dose rate calculations.
*Default*: False
.. _verbosity:
-----------------------
@ -1465,7 +1731,8 @@ sub-elements/attributes:
*Default*: None
:particle_type:
The particle that the weight windows will apply to (e.g., 'neutron')
The particle that the weight windows will apply to, specified as a PDG
code or string (e.g., ``neutron``).
*Default*: 'neutron'
@ -1525,7 +1792,8 @@ mesh-based weight windows.
*Default*: None
:particle_type:
The particle that the weight windows will apply to (e.g., 'neutron')
The particle that the weight windows will apply to, specified as a PDG
code or string (e.g., ``neutron``).
*Default*: neutron
@ -1569,6 +1837,14 @@ mesh-based weight windows.
*Default*: 5.0
For FW-CADIS:
:targets:
A sequence of IDs corresponding to the tallies which cover phase
space regions of interest for local variance reduction.
*Default*: None
---------------------------------------
``<weight_window_checkpoints>`` Element
---------------------------------------
@ -1594,3 +1870,21 @@ following sub-elements/attributes:
The ``weight_windows_file`` element has no attributes and contains the path to
a weight windows HDF5 file to load during simulation initialization.
-------------------------------
``<weight_windows_on>`` Element
-------------------------------
The ``weight_windows_on`` element indicates whether weight windows are
enabled.
*Default*: False
----------------------------------
``<write_initial_source>`` Element
----------------------------------
The ``write_initial_source`` element indicates whether to write the initial
source distribution to file.
*Default*: False

View file

@ -15,6 +15,8 @@ following the same format.
**/**
:Attributes: - **filetype** (*char[]*) -- String indicating the type of file.
- **version** (*int[2]*) -- Major and minor version of the source
file format.
:Datasets:
@ -22,5 +24,5 @@ following the same format.
particle. The compound type has fields ``r``, ``u``, ``E``,
``time``, ``wgt``, ``delayed_group``, ``surf_id`` and ``particle``,
which represent the position, direction, energy, time, weight,
delayed group, surface ID, and particle type (0=neutron, 1=photon,
2=electron, 3=positron), respectively.
delayed group, surface ID, and particle type (PDG number),
respectively.

View file

@ -4,7 +4,7 @@
State Point File Format
=======================
The current version of the statepoint file format is 18.1.
The current version of the statepoint file format is 18.2.
**/**
@ -56,8 +56,8 @@ The current version of the statepoint file format is 18.1.
``time``, ``wgt``, ``delayed_group``, ``surf_id``, and
``particle``, which represent the position, direction, energy,
time, weight, delayed group, surface ID, and particle type
(0=neutron, 1=photon, 2=electron, 3=positron), respectively. Only
present when `run_mode` is 'eigenvalue'.
(PDG number), respectively. Only present when `run_mode` is
'eigenvalue'.
**/tallies/**

View file

@ -142,9 +142,9 @@ attributes/sub-elements:
:type:
The type of the filter. Accepted options are "cell", "cellfrom",
"cellborn", "surface", "material", "universe", "energy", "energyout", "mu",
"polar", "azimuthal", "mesh", "distribcell", "delayedgroup",
"energyfunction", and "particle".
"cellborn", "surface", "material", "universe", "energy", "energyout",
"mu", "polar", "azimuthal", "mesh", "distribcell", "delayedgroup",
"energyfunction", "particle", and "particleproduction".
:bins:
A description of the bins for each type of filter can be found in
@ -318,8 +318,34 @@ should be set to:
they use ``energy`` and ``y``.
:particle:
A list of integers indicating the type of particles to tally ('neutron' = 1,
'photon' = 2, 'electron' = 3, 'positron' = 4).
A list of particle identifiers to tally, specified as strings (e.g.,
``neutron``, ``photon``, ``He4``) or as integer PDG numbers.
:particleproduction:
This filter tallies secondary particles produced in reactions, binned by
particle type and, optionally, by energy. Unlike other energy filters, the
weight applied is the weight of the secondary particle. To obtain secondary
particle production rates, use this filter with the ``events`` score.
The filter uses the following sub-elements instead of ``bins``:
:particles:
A space-separated list of secondary particle types to tally (e.g.,
``photon``, ``neutron``, ``electron``).
:energies:
An optional monotonically increasing list of energy boundaries in [eV]
for binning the secondary particle energies. If omitted, total production
is tallied without energy binning.
For example, to tally photon and neutron production in three energy groups:
.. code-block:: xml
<filter id="1" type="particleproduction">
<particles>photon neutron</particles>
<energies>0.0 1.0e5 1.0e6 20.0e6</energies>
</filter>
------------------
``<mesh>`` Element

View file

@ -4,7 +4,7 @@
Track File Format
=================
The current revision of the particle track file format is 3.0.
The current revision of the particle track file format is 3.1.
**/**
@ -32,6 +32,5 @@ The current revision of the particle track file format is 3.0.
the array for each primary/secondary particle. The
last offset should match the total size of the
array.
- **particles** (*int[]*) -- Particle type for each
primary/secondary particle (0=neutron, 1=photon,
2=electron, 3=positron).
- **particles** (*int32_t[]*) -- Particle type for
each primary/secondary particle (PDG number).

View file

@ -4,7 +4,7 @@
License Agreement
=================
Copyright © 2011-2025 Massachusetts Institute of Technology, UChicago Argonne
Copyright © 2011-2026 Massachusetts Institute of Technology, UChicago Argonne
LLC, and OpenMC contributors
Permission is hereby granted, free of charge, to any person obtaining a copy of

View file

@ -289,6 +289,48 @@ sections. This allows flexibility for the model to use highly anisotropic
scattering information in the water while the fuel can be simulated with linear
or even isotropic scattering.
Particle Speed
--------------
When using a multigroup representation of cross sections, the particle speed has
meaning only in an average sense. The particle speed is important when modeling
dynamic behavior. OpenMC calculates the particle speed using the inverse
velocity multigroup data if it is available. If such data is not available,
OpenMC uses an approximate velocity using the group energy bounds in the
following way:
.. math::
\frac{1}{v_g} = \int_{E_{\text{min}}^g}^{E_{\text{max}}^g} \frac{1}{v(E)} \frac{\alpha}{E} dE
Where :math:`E_{\text{min}}^g` and :math:`E_{\text{max}}^g` are the group energy
boundaries for group :math:`g`. :math:`v(E)` is the neutron velocity calculated
using relativistic kinematics, :math:`\alpha` is a normalization constant for the
:math:`\frac{1}{E}` spectrum.
This equation is valid when inside the group boundaries the neutron spectrum
follows a typical :math:`\frac{1}{E}` slowing down spectrum. This assumption is
widely used when generating fine group neutron cross section data libraries from
continuous energy data.
The solution to this equation is:
.. math::
\frac{1}{v_g} = \frac{1}{c \log\left(\frac{E_{\text{max}}^g}{E_{\text{min}}^g}\right)}
\left[ 2(\operatorname{arctanh}(k_{\text{max}}^{-1}) - \operatorname{arctanh}(k_{\text{min}}^{-1}))
- (k_{\text{max}}-k_{\text{min}}) \right]
where :math:`c` is the speed of light and :math:`k_{\text{max}}`,
:math:`k_{\text{min}}` are defined by a change of variables:
.. math::
k = \sqrt{1+\frac{2 m_n c^2}{E}}
where :math:`E` is the particle kinetic energy and :math:`m_n` is the neutron
rest mass.
.. _logarithmic mapping technique:
https://mcnp.lanl.gov/pdf_files/TechReport_2014_LANL_LA-UR-14-24530_Brown.pdf
.. _Hwang: https://doi.org/10.13182/NSE87-A16381

View file

@ -1081,28 +1081,32 @@ lifetimes.
In OpenMC, the random ray adjoint solver is implemented simply by transposing
the scattering matrix, swapping :math:`\nu\Sigma_f` and :math:`\chi`, and then
running a normal transport solve. When no external fixed source is present, no
additional changes are needed in the transport process. However, if an external
fixed forward source is present in the simulation problem, then an additional
step is taken to compute the accompanying fixed adjoint source. In OpenMC, the
adjoint flux does *not* represent a response function for a particular detector
region. Rather, the adjoint flux is the global response, making it appropriate
for use with weight window generation schemes for global variance reduction.
Thus, if using a fixed source, the external source for the adjoint mode is
simply computed as being :math:`1 / \phi`, where :math:`\phi` is the forward
scalar flux that results from a normal forward solve (which OpenMC will run
first automatically when in adjoint mode). The adjoint external source will be
computed for each source region in the simulation mesh, independent of any
tallies. The adjoint external source is always flat, even when a linear
scattering and fission source shape is used. When in adjoint mode, all reported
results (e.g., tallies, eigenvalues, etc.) are derived from the adjoint flux,
even when the physical meaning is not necessarily obvious. These values are
still reported, though we emphasize that the primary use case for adjoint mode
is for producing adjoint flux tallies to support subsequent perturbation studies
and weight window generation.
running a normal transport solve. When no external fixed forward source is
present, or if an adjoint fixed source is specifically provided, no additional
changes are needed in the transport process. This adjoint source can
correspond, for example, to a detector response function in a particular
region. However, if an external fixed forward source is present in the
simulation problem without an adjoint fixed source, an additional step is taken
to compute the accompanying forward-weighted adjoint source. In this case, the
adjoint flux does *not* represent the importance of locations in phase space to
detector response; rather, the "response" in question is a uniform distribution
of Monte Carlo particle density, making the importance provided by the adjoint
flux appropriate for use with weight window generation schemes for global
variance reduction. Thus, if using a fixed source, the forward-weighted
external source for adjoint mode is simply computed as being :math:`1 / \phi`,
where :math:`\phi` is the forward scalar flux that results from a normal
forward solve (which OpenMC will run first automatically when in adjoint mode).
The adjoint external source will be computed for each source region in the
simulation mesh, independent of any tallies. The adjoint external source is
always flat, even when a linear scattering and fission source shape is used.
Note that the adjoint :math:`k_{eff}` is statistically the same as the forward
:math:`k_{eff}`, despite the flux distributions taking different shapes.
When in adjoint mode, all reported results (e.g., tallies, eigenvalues, etc.)
are derived from the adjoint flux, even when the physical meaning is not
necessarily obvious. These values are still reported, though we emphasize that
the primary use case for adjoint mode is for producing adjoint flux tallies to
support subsequent perturbation studies and weight window generation. Note
however that the adjoint :math:`k_{eff}` is statistically the same as the
forward :math:`k_{eff}`, despite the flux distributions taking different shapes.
---------------------------
Fundamental Sources of Bias

View file

@ -205,7 +205,71 @@ had a collision at every event. Thus, for tallies with outgoing-energy filters
or for tallies of scattering moments (which require the scattering cosine of
the change-in-angle), we must use an analog estimator.
.. TODO: Add description of surface current tallies
-----------------------------------
Surface-Integrated Flux and Current
-----------------------------------
Surface tallies allow you to measure particle behavior as they cross specific
boundaries in your geometry. Unlike volume tallies, which integrate over a
volumetric region, surface tallies capture the current or flux passing through a
surface. Surface tallies are estimated using an analog estimator.
Current Score
-------------
When tallying the current across a surface, we simply count the weight of
particles that cross the surface of interest:
.. math::
:label: analog-current-estimator
J = \frac{1}{W} \sum_{i \in S} w_i.
where :math:`J` is the area-integrated current passing through surface
:math:`S`, :math:`W` is the total starting weight of the particles, and
:math:`w_i` is the weight of the particle as it crosses the surface :math:`S`.
Flux Score
----------
When tallying flux over a surface, we use the relationship between current and
flux:
.. math::
:label: surface-flux-estimator
\phi_S = \frac{1}{W} \sum_{i \in S} \frac{w_i}{|\mu|}.
where :math:`\phi_S` is the area-integrated flux over surface :math:`S`,
:math:`W` is the total starting weight of the particles, :math:`w_i` is the
weight of the particle as it crosses the surface :math:`S` and :math:`\mu` is
the cosine of angle between the particle direction and the surface normal.
This equation diverges when the particle crossing the surface is nearly parallel
to it (that is, as :math:`\mu` approaches zero). To remove this divergence,
OpenMC scores:
.. math::
:label: modified-surface-flux-estimator
\phi_S = \frac{1}{W} \sum_{i \in S} w_i f(\mu).
and the function :math:`f` is defined by:
.. math::
f(\mu) = \begin{cases}
\frac{1}{|\mu|} & |\mu| > \mu_\text{cut} \\
\frac{1}{c\mu_\text{cut}} & |\mu| \le \mu_\text{cut}
\end{cases}
where :math:`\mu_\text{cut}` is the grazing cosine cutoff and :math:`c` is the
cosine substitution ratio. The parameters :math:`\mu_\text{cut}` and :math:`c`
can be set by the user via the :attr:`openmc.Settings.surface_grazing_cutoff`
and :attr:`openmc.Settings.surface_grazing_ratio` attributes, respectively. The
default values for these parameters are 0.001 and 0.5 as recommended by
`Favorite, Thomas, and Booth <https://doi.org/10.13182/NSE09-72>`_.
.. _tallies_statistics:

View file

@ -22,12 +22,14 @@ not experience a single scoring event, even after billions of analog histories.
Variance reduction techniques aim to either flatten the global uncertainty
distribution, such that all regions of phase space have a fairly similar
uncertainty, or to reduce the uncertainty in specific locations (such as a
detector). There are two strategies available in OpenMC for variance reduction:
the Monte Carlo MAGIC method and the FW-CADIS method. Both strategies work by
developing a weight window mesh that can be utilized by subsequent Monte Carlo
solves to split particles heading towards areas of lower flux densities while
terminating particles in higher flux regions---all while maintaining a fair
game.
detector). There are three strategies available in OpenMC for variance
reduction: weight windows generated via the MAGIC method or the FW-CADIS method,
and source biasing. Both weight windowing strategies work by developing a mesh
that can be utilized by subsequent Monte Carlo solves to split particles heading
towards areas of lower flux densities while terminating particles in higher flux
regions. In contrast, source biasing modifies source site sampling behavior to
preferentially track particles more likely to reach phase space regions of
interest.
------------
MAGIC Method
@ -80,8 +82,8 @@ where it was born from.
The Forward-Weighted Consistent Adjoint Driven Importance Sampling method, or
`FW-CADIS method <https://doi.org/10.13182/NSE12-33>`_, produces weight windows
for global variance reduction given adjoint flux information throughout the
entire domain. The weight window lower bound is defined in Equation
for global or local variance reduction given adjoint flux information throughout
the entire domain. The weight window lower bound is defined in Equation
:eq:`fw_cadis`, and also involves a normalization step not shown here.
.. math::
@ -132,3 +134,83 @@ aware of this.
:label: variance_fom
\text{FOM} = \frac{1}{\text{Time} \times \sigma^2}
Finally, one unique capability of the FW-CADIS weight window generator is to
produce weight windows for local variance reduction, given a list of the
responses of interest. This is controlled by optionally specifying target
tallies from the :class:`openmc.model.Model` to the
:class:`openmc.WeightWindowGenerator`, as illustrated in the
:ref:`user guide<variance_reduction>`. If target tallies for local variance
reduction are supplied, then the adjoint sources are only populated after the
initial forward simulation in the source regions associated with those tallies.
In other regions, the adjoint source term is instead set to zero. The Random
Ray solver then determines the adjoint flux map used to generate FW-CADIS
weight windows following the usual technique.
.. _methods_source_biasing:
--------------
Source Biasing
--------------
In contrast to the previous two methods that introduce population controls
during transport, source biasing modifies the sampling of the external source
distribution. The basic premise of the technique is that for each spatial,
angular, energy, or time distribution of a source, an additional distribution
can be specified provided that the two share a common support (set of points
where the distribution is nonzero). Samples are then drawn from this "bias"
distribution, which can be chosen to preferentially direct particles towards
phase space regions of interest. In order to avoid biasing the tally results,
however, a weight adjustment is applied to each sampled site as described below.
Assume that the unbiased probability density function of a random variable
:math:`X:x \rightarrow \mathbb{R}` is given by :math:`f(x)`, but that using the
biased distribution :math:`g(x)` will result in a greater number of particle
trajectories reaching some phase space region of interest. Then a sample
:math:`x_0` may be drawn from :math:`g(x)` while maintaining a fair game,
provided that its weight is adjusted as:
.. math::
:label: source_bias
w = w_0 \times \frac{f(x_0)}{g(x_0)}
where :math:`w_0` is the weight of an unbiased sample from :math:`f(x)`,
typically unity.
Returning now to Equation :eq:`source_bias`, the requirement for common support
becomes evident. If :math:`\mathrm{supp} (g)` fully contains but is not
identical to :math:`\mathrm{supp} (f)`, then some samples from :math:`g(x)` will
correspond to points where :math:`f(x) = 0`. Thus these source sites would be
assigned a starting weight of 0, meaning the particles would be killed
immediately upon transport, effectively wasting computation time. Conversely, if
:math:`\mathrm{supp} (g)` is fully contained by but not identical to
:math:`\mathrm{supp} (f)`, the contributions of some regions outside
:math:`\mathrm{supp} (g)` will not be counted towards the integral, potentially
biasing the tally. The weight assigned to such points would be undefined since
:math:`g(x) = \mathbf{0}` at these points.
When an independent source is sampled in OpenMC, the particle's coordinate in
each variable of phase space :math:`(\mathbf{r},\mathbf{\Omega},E,t)` is
successively drawn from an independent probability distribution. Multiple
variables can be biased, in which case the resultant weight :math:`w` applied to
the particle is the product of the weights assigned from all sampled
distributions: space, angle, energy, and time, as shown in Equation
:eq:`tot_wgt`.
.. math::
:label: tot_wgt
w = w_r \times w_{\Omega} \times w_E \times w_t
Finally, source biasing and weight windows serve different purposes. Source
biasing changes how particles are born, allowing the initial source sites to be
sampled preferentially from important regions of phase space (space, angle,
energy, and time) with an accompanying weight adjustment. Weight windows, by
contrast, apply population control during transport (splitting and Russian
roulette) to help particles reach and contribute in important regions as they
move through the system. Because particle transport proceeds as usual after a
biased source is sampled, particle attenuation in optically thick regions
outside the source volume will not be affected by source biasing; in such
scenarios, transport biasing techniques such as weight windows are often more
effective.

View file

@ -26,6 +26,7 @@ Simulation Settings
openmc.FileSource
openmc.CompiledSource
openmc.MeshSource
openmc.TokamakSource
openmc.SourceParticle
openmc.VolumeCalculation
openmc.Settings
@ -132,6 +133,7 @@ Constructing Tallies
openmc.MeshSurfaceFilter
openmc.EnergyFilter
openmc.EnergyoutFilter
openmc.ParticleProductionFilter
openmc.MuFilter
openmc.MuSurfaceFilter
openmc.PolarFilter
@ -148,6 +150,7 @@ Constructing Tallies
openmc.ZernikeRadialFilter
openmc.ParentNuclideFilter
openmc.ParticleFilter
openmc.ReactionFilter
openmc.MeshMaterialVolumes
openmc.Trigger
openmc.TallyDerivative
@ -176,7 +179,8 @@ Geometry Plotting
:nosignatures:
:template: myclass.rst
openmc.Plot
openmc.SlicePlot
openmc.VoxelPlot
openmc.WireframeRayTracePlot
openmc.SolidRayTracePlot
openmc.Plots

View file

@ -40,6 +40,7 @@ Functions
reset_timers
run
run_in_memory
run_random_ray
sample_external_source
simulation_finalize
simulation_init
@ -81,12 +82,15 @@ Classes
Nuclide
ParentNuclideFilter
ParticleFilter
ParticleProductionFilter
PolarFilter
ReactionFilter
RectilinearMesh
RegularMesh
SpatialLegendreFilter
SphericalHarmonicsFilter
SphericalMesh
SolidRayTracePlot
SurfaceFilter
Tally
TemporarySession
@ -124,6 +128,12 @@ Data
:type: dict
.. data:: plots
Mapping of plot ID to :class:`openmc.lib.SolidRayTracePlot` instances.
:type: dict
.. data:: nuclides
Mapping of nuclide name to :class:`openmc.lib.Nuclide` instances.

View file

@ -71,6 +71,8 @@ Core Functions
isotopes
kalbach_slope
linearize
mass_attenuation_coefficient
mass_energy_absorption_coefficient
thin
water_density
zam

View file

@ -11,6 +11,16 @@ Module Variables
.. autodata:: openmc.mgxs.GROUP_STRUCTURES
:annotation:
Functions
+++++++++
.. autosummary::
:toctree: generated
:nosignatures:
:template: myfunction.rst
openmc.mgxs.convert_flux_groups
Classes
+++++++

View file

@ -22,6 +22,7 @@ Univariate Probability Distributions
openmc.stats.Legendre
openmc.stats.Mixture
openmc.stats.Normal
openmc.stats.DecaySpectrum
.. autosummary::
:toctree: generated
@ -29,6 +30,7 @@ Univariate Probability Distributions
:template: myfunction.rst
openmc.stats.delta_function
openmc.stats.fusion_neutron_spectrum
openmc.stats.muir
Angular Distributions
@ -67,3 +69,4 @@ Spatial Distributions
:template: myfunction.rst
openmc.stats.spherical_uniform
openmc.stats.cylindrical_uniform

View file

@ -119,7 +119,7 @@ packages should be installed, for example in Homebrew via:
.. code-block:: sh
brew install llvm cmake xtensor hdf5 python libomp libpng
brew install llvm cmake hdf5 python libomp libpng
The compiler provided by the above LLVM package should be used in place of the
one provisioned by XCode, which does not support the multithreading library used

View file

@ -132,8 +132,9 @@ can be run::
r2s.run(timesteps, source_rates, bounding_boxes=bounding_boxes)
If not specified otherwise, a photon transport calculation is run at each time
in the depletion schedule. That means in the case above, we would see three
photon transport calculations. To specify specific times at which photon
in the depletion schedule for which a decay photon source exists. Times without
a decay photon source, such as the initial state of a model containing only
stable nuclides, are omitted. To specify particular times at which photon
transport calculations should be run, pass the ``photon_time_indices`` argument.
For example, if we wanted to run a photon transport calculation only on the last
time (after the 5 hour decay), we would run::
@ -141,6 +142,19 @@ time (after the 5 hour decay), we would run::
r2s.run(timesteps, source_rates, bounding_boxes=bounding_boxes,
photon_time_indices=[2])
To attribute photon tally results to their parent radionuclides, set
``by_parent_nuclide=True``. This automatically adds a
:class:`openmc.ParentNuclideFilter` to every photon tally that does not already
have one. The filter bins are the union of radionuclides contributing to the
prepared decay photon sources. The resulting bins can be used directly when
inspecting the tally results::
r2s.run(timesteps, source_rates, bounding_boxes=bounding_boxes,
photon_time_indices=[2], by_parent_nuclide=True)
photon_tally = r2s.results['photon_tallies'][2][0]
tally_by_parent = photon_tally.get_pandas_dataframe()
After an R2S calculation has been run, the :class:`~openmc.deplete.R2SManager`
instance will have a ``results`` dictionary that allows you to directly access
results from each of the steps. It will also write out all the output files into
@ -148,12 +162,13 @@ a directory that is named "r2s_<timestamp>/". The ``output_dir`` argument to the
:meth:`~openmc.deplete.R2SManager.run` method enables you to override the
default output directory name if desired.
The :meth:`~openmc.deplete.R2SManager.run` method actually runs three
The :meth:`~openmc.deplete.R2SManager.run` method actually runs four
lower-level methods under the hood::
r2s.step1_neutron_transport(...)
r2s.step2_activation(...)
r2s.step3_photon_transport(...)
r2s.step3_photon_source(...)
r2s.step4_photon_transport(...)
For users looking for more control over the calculation, these lower-level
methods can be used in lieu of the :meth:`openmc.deplete.R2SManager.run` method.
@ -190,6 +205,25 @@ we would run::
r2s.run(timesteps, source_rates, mat_vol_kwargs={'n_samples': 10_000_000})
It is also possible to use multiple meshes by passing a list of meshes instead
of a single mesh. This can be useful, for example, when different regions of the
model require different mesh resolutions. The meshes are assumed to be
**non-overlapping**; each element--material combination across all meshes is
treated as an independent activation region, and all meshes are handled in a
single neutron transport solve. For example::
# Fine mesh near the activation target
mesh_fine = openmc.RegularMesh()
mesh_fine.dimension = (10, 10, 10)
...
# Coarse mesh for the surrounding region
mesh_coarse = openmc.RegularMesh()
mesh_coarse.dimension = (5, 5, 5)
...
r2s = openmc.deplete.R2SManager(model, [mesh_fine, mesh_coarse])
Direct 1-Step (D1S) Calculations
================================
@ -236,4 +270,3 @@ relevant tallies. This can be done with the aid of the
# Apply time correction factors
tally = d1s.apply_time_correction(dose_tally, factors, time_index)

View file

@ -449,3 +449,42 @@ to transfer xenon from one material to another, you'd use::
...
integrator.add_transfer_rate(mat1, ['Xe'], 0.1, destination_material=mat2)
Comparing to Other Codes
========================
Comparing depletion results from OpenMC with those from another code, such as
MCNP or Serpent, requires more than constructing equivalent transport models.
At each depletion step, differences in the transport solution, nuclear data,
reaction rate normalization, and numerical integration can all affect the
result. Small differences can also accumulate over successive depletion steps.
For a meaningful comparison, align as many of the following inputs and methods
as possible:
- Geometry and material definitions and associated physical properties such as
temperature
- Neutron cross section library (e.g., ENDF/B-VIII.0)
- Treatment of thermal scattering and unresolved resonance probability tables
- Neutron reactions accounted for in the depletion chain
- Decay data in the depletion chain
- Isomeric branching ratios for reactions in the depletion chain
- Fission product yields in the depletion chain
- Fission product yield interpolation method
(``CoupledOperator(fission_yield_mode=...)``)
- Reaction rate normalization, including fission Q values
(``CoupledOperator(fission_q=...)``)
- Depletion integration method (``PredictorIntegrator``, ``CECMIntegrator``,
etc.) and time-step sizes
When comparing to codes that use ACE format cross sections, it is recommended to
directly convert the ACE files to HDF5 format using functionality from the
:mod:`openmc.data` module (see :ref:`create_xs_library`). Some of the
LANL-distributed ACE libraries used with MCNP have also been converted to HDF5
format and are available for download at https://openmc.org/data.
Even after these choices have been aligned, exact agreement should not be
expected. Codes may use different approximations or numerical methods that
cannot be configured identically. When investigating a discrepancy, first
compare transport results and one-group reaction rates at the initial time, then
compare changes over subsequent timesteps.

View file

@ -182,6 +182,8 @@ boundary condition.
Periodic boundary conditions can be applied to pairs of planar surfaces.
If there are only two periodic surfaces they will be matched automatically.
Otherwise it is necessary to specify pairs explicitly using the
:attr:`Surface.periodic_surface` attribute as in the following example::
@ -192,7 +194,7 @@ Otherwise it is necessary to specify pairs explicitly using the
Both rotational and translational periodic boundary conditions are specified in
the same fashion. If both planes have the same normal vector, a translational
periodicity is assumed; rotational periodicity is assumed otherwise. Currently,
only rotations about the :math:`z`-axis are supported.
rotations must be about the :math:`x`-, :math:`y`-, or :math:`z`-axis.
For a rotational periodic BC, the normal vectors of each surface must point
inwards---towards the valid geometry. For example, a :class:`XPlane` and
@ -246,6 +248,28 @@ The classes :class:`Halfspace`, :class:`Intersection`, :class:`Union`, and
:class:`Complement` and all instances of :class:`openmc.Region` and can be
assigned to the :attr:`Cell.region` attribute.
Cells also contain :attr:`Cell.temperature` and :attr:`Cell.density`
attributes which override the temperature and density of the fill. These can
be quite useful when temperatures and densities are spatially varying, as the
alternative would be to add a unique :class:`Material` for each permutation of
temperature, density, and composition. You can set the temperature (K) and
density (g/cc) of a cell like so::
fuel.temperature = 800.0
fuel.density = 10.0
The real utility of cell temperatures and densities occurs when a cell is
replicated across the geometry, such as when a cell is the root geometric element
in a replicated :ref:`universe<usersguide_universes>` or :ref:`lattice
<usersguide_lattices>`. In those cases, you can provide a list of temperatures
and densities to apply a temperature/density field to all of the distributed cells::
fuel.temperature = [800.0, 900.0, 800.0, 900.0]
fuel.density = [10.0, 9.0, 10.0, 9.0]
In this example, the fuel cell is distributed four times in the geometry. Each
distributed instance then receives its own temperature and density.
.. _usersguide_universes:
---------
@ -413,11 +437,11 @@ to help figure out how to place universes::
Note that by default, hexagonal lattices are positioned such that each lattice
element has two faces that are parallel to the :math:`y` axis. As one example,
to create a three-ring lattice centered at the origin with a pitch of 10 cm
where all the lattice elements centered along the :math:`y` axis are filled with
universe ``u`` and the remainder are filled with universe ``q``, the following
code would work::
element has two faces that are perpendicular to the :math:`y` axis. As one
example, to create a three-ring lattice centered at the origin with a pitch of
10 cm where all the lattice elements centered along the :math:`y` axis are
filled with universe ``u`` and the remainder are filled with universe ``q``, the
following code would work::
hexlat = openmc.HexLattice()
hexlat.center = (0, 0)
@ -530,6 +554,89 @@ UWUW and OpenMC material ID space will cause an error. To automatically resolve
these ID overlaps, ``auto_ids`` can be set to ``True`` to append the UWUW
material IDs to the OpenMC material ID space.
Material overrides and differentiation
--------------------------------------
Programmatic access to DAGMC cell information for material overrides
and differentiation requires synchronization of the DAGMC universe
representation across Python and C-API::
model.init_lib()
model.sync_dagmc_universes()
model.finalize_lib()
Upon completion of these steps, the :attr:`DAGMCUniverse.cells` attribute will
be populated with :class:`DAGMCCell` proxy objects that represent the cells
defined in the DAGMC model. The :class:`DAGMCCell` objects will have
:class:`openmc.Material`'s' applied according to the assignments upon
initialization of the model. These materials can be replaced in the same manner
as :class:`openmc.Cell` objects to override material assignments in the DAGMC
model.
Depletion with DAGMC geometry
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The synchronization of :class:`openmc.DAGMCUniverse`'s is important for
depletion calculations using DAGMC geometry when materials need to be
differentiated to perform material burnup independently in each DAGMC cell. See
:meth:`openmc.model.Model.differentiate_mats`.
Material overrides
~~~~~~~~~~~~~~~~~~
OpenMC supports overriding material assignments defined inside a DAGMC HDF5
model so that CAD-assigned materials can be replaced by :class:`openmc.Material`
objects. This is useful when the CAD geometry provides the shape but OpenMC
materials (specific nuclide content, densities, or depletion behavior) are
required.
Replacing materials by name
^^^^^^^^^^^^^^^^^^^^^^^^^^^
If a DAGMC file includes material name tags, you can replace all cells that
reference a particular name with an :class:`openmc.Material` using
:meth:`~openmc.DAGMCUniverse.replace_material_assignment`::
import openmc
dag_univ = openmc.DAGMCUniverse('dagmc.h5m')
fuel = openmc.Material(name='fuel')
fuel.add_nuclide('U235', 0.05)
fuel.add_nuclide('U238', 0.95)
fuel.set_density('g/cm3', 10.5)
dag_univ.replace_material_assignment('Fuel', fuel)
This lets you keep CAD geometry while adopting OpenMC material definitions.
Per-cell material overrides
^^^^^^^^^^^^^^^^^^^^^^^^^^^
To assign overrides without initializing :class:`openmc.Model`, the
:meth:`openmc.DAGMCUniverse.add_material_override` method can be used to assign
materials to particular DAGMC cells. The method accepts either an integer cell
ID::
dag_univ = openmc.DAGMCUniverse('dagmc.h5m')
enriched = openmc.Material(name='fuel_enriched')
enriched.add_nuclide('U235', 0.10)
enriched.add_nuclide('U238', 0.90)
enriched.set_density('g/cm3', 10.5)
dag_univ.add_material_override(1, enriched)
In the case that the :class:`openmc.DAGMCUniverse` has already been synchronized,
a :class:`openmc.DAGMCCell` object can also be provide to assign the material.
Overrides are written to the `<material_overrides>` element of the
:ref:`<dagmc_universe> <dagmc_element>` XML element so the C++ core can apply
them on initialization.
.. _Direct Accelerated Geometry Monte Carlo: https://svalinn.github.io/DAGMC/
.. _University of Wisconsin Unified Workflow: https://svalinn.github.io/DAGMC/usersguide/uw2.html

View file

@ -158,6 +158,75 @@ feature can be used to access the installed packages.
.. _Spack: https://spack.readthedocs.io/en/latest/
.. _setup guide: https://spack.readthedocs.io/en/latest/getting_started.html
.. _install_aur:
------------------------------------
Installing on Arch Linux via the AUR
------------------------------------
On Arch Linux and Arch-based distributions, OpenMC can be installed from the
`Arch User Repository (AUR) <https://aur.archlinux.org/>`_. An AUR package named
``openmc-git`` is available, which builds OpenMC directly from the latest
development sources.
This package provides a full-featured OpenMC stack, including:
* MPI and DAGMC-enabled OpenMC build
* User-selected nuclear data libraries
* The `CAD_to_OpenMC <https://github.com/united-neux/CAD_to_OpenMC>`_ meshing tool
* All required dependencies for the above components
To install the package, you will need an AUR helper such as `yay`_ or `paru`_.
For example, using ``yay``::
yay -S openmc-git
Alternatively, you can manually clone and build the package::
git clone https://aur.archlinux.org/openmc-git.git
cd openmc-git
makepkg -si
Note, ``makepkg`` uses ``pacman`` to resolve dependencies. Therefore, AUR-based
dependencies need to be installed separately with ``yay`` or ``paru`` before
running ``makepkg``. The PKGBUILD will automatically handle all required
dependencies and build OpenMC with MPI and DAGMC support enabled.
.. tip::
If there are failing checks during the build process, you can bypass them
with the ``--nocheck`` flag::
yay -S openmc-git --mflags "--nocheck"
Or::
git clone https://aur.archlinux.org/openmc-git.git
cd openmc-git
makepkg -si --nocheck
.. note::
The ``openmc-git`` package tracks the latest development version from the
upstream repository. As such, it may include new features and bug fixes, but
could also introduce instability compared to official releases.
.. tip::
OpenMC is installed under ``/opt``. If you are installing and using it in
the same terminal session, you may need to reload your environment
variables::
source /etc/profile
Alternatively, start a new shell session.
Once installed, the ``openmc`` executable, nuclear data libraries, and
associated tools will be available in your system :envvar:`PATH`.
.. _yay: https://github.com/Jguer/yay
.. _paru: https://github.com/Morganamilo/paru
.. _install_source:
@ -262,11 +331,11 @@ Prerequisites
This option allows OpenMC to read and write MCPL (Monte Carlo Particle
Lists) files instead of .h5 files for sources (external source
distribution, k-eigenvalue source distribution, and surface sources). To
turn this option on in the CMake configuration step, add the following
option::
cmake -DOPENMC_USE_MCPL=on ..
distribution, k-eigenvalue source distribution, and surface sources).
OpenMC does not need any particular build option to use this, but MCPL
must be installed on the system in order to do so. Refer to the
`MCPL documentation <https://github.com/mctools/mcpl/blob/HEAD/INSTALL.md>`_
for instructions on how to accomplish this.
* NCrystal_ library for defining materials with enhanced thermal neutron transport
@ -383,6 +452,20 @@ OPENMC_USE_MPI
options, please see the `FindMPI.cmake documentation
<https://cmake.org/cmake/help/latest/module/FindMPI.html>`_.
.. _cmake_strict_fp:
OPENMC_ENABLE_STRICT_FP
Disables compiler optimizations that change floating-point results relative to
unoptimized builds, improving cross-platform and cross-optimization-level
reproducibility. This disables FMA contraction (``-ffp-contract=off``) and
compiler builtin replacements of math functions like ``pow``, ``exp``, ``log``
(``-fno-builtin``). It also keeps C/C++ assertions active by removing the
``-DNDEBUG`` flag from ``RelWithDebInfo`` builds. Without this flag, these
optimizations can produce bit-level differences across platforms, compilers,
and optimization levels. This option should be used when running the test
suite. By default (off), the compiler is free to use all optimizations for
best performance. (Default: off)
OPENMC_FORCE_VENDORED_LIBS
Forces OpenMC to use the submodules located in the vendor directory, as
opposed to searching the system for already installed versions of those
@ -415,7 +498,10 @@ Release
RelWithDebInfo
(Default if no type is specified.) Enable optimization and debug. On most
platforms/compilers, this is equivalent to `-O2 -g`.
platforms/compilers, this is equivalent to `-O2 -g`. When
:ref:`OPENMC_ENABLE_STRICT_FP <cmake_strict_fp>` is enabled, OpenMC removes the
``-DNDEBUG`` flag that CMake normally adds for this build type, so that
C/C++ assertions remain active.
Example of configuring for Debug mode:

View file

@ -6,13 +6,14 @@ Geometry Visualization
.. currentmodule:: openmc
OpenMC is capable of producing two-dimensional slice plots of a geometry as well
as three-dimensional voxel plots using the geometry plotting :ref:`run mode
<usersguide_run_modes>`. The geometry plotting mode relies on the presence of a
:ref:`plots.xml <io_plots>` file that indicates what plots should be created. To
create this file, one needs to create one or more :class:`openmc.Plot`
instances, add them to a :class:`openmc.Plots` collection, and then use the
:class:`Plots.export_to_xml` method to write the ``plots.xml`` file.
OpenMC is capable of producing two-dimensional slice plots of a geometry,
three-dimensional voxel plots, and three-dimensional raytrace plots using the
geometry plotting :ref:`run mode <usersguide_run_modes>`. The geometry plotting
mode relies on the presence of a :ref:`plots.xml <io_plots>` file that indicates
what plots should be created. To create this file, one needs to create one or
more instances of the various plot classes described below, add them to a
:class:`openmc.Plots` collection, and then use the :class:`Plots.export_to_xml`
method to write the ``plots.xml`` file.
-----------
Slice Plots
@ -21,15 +22,14 @@ Slice Plots
.. image:: ../_images/atr.png
:width: 300px
By default, when an instance of :class:`openmc.Plot` is created, it indicates
that a 2D slice plot should be made. You can specify the origin of the plot
(:attr:`Plot.origin`), the width of the plot in each direction
(:attr:`Plot.width`), the number of pixels to use in each direction
(:attr:`Plot.pixels`), and the basis directions for the plot. For example, to
create a :math:`x` - :math:`z` plot centered at (5.0, 2.0, 3.0) with a width of
(50., 50.) and 400x400 pixels::
The :class:`openmc.SlicePlot` class indicates that a 2D slice plot should be
made. You can specify the origin of the plot (:attr:`SlicePlot.origin`), the
width of the plot in each direction (:attr:`SlicePlot.width`), the number of
pixels to use in each direction (:attr:`SlicePlot.pixels`), and the basis
directions for the plot. For example, to create a :math:`x` - :math:`z` plot
centered at (5.0, 2.0, 3.0) with a width of (50., 50.) and 400x400 pixels::
plot = openmc.Plot()
plot = openmc.SlicePlot()
plot.basis = 'xz'
plot.origin = (5.0, 2.0, 3.0)
plot.width = (50., 50.)
@ -47,7 +47,7 @@ that location.
By default, a unique color will be assigned to each cell in the geometry. If you
want your plot to be colored by material instead, change the
:attr:`Plot.color_by` attribute::
:attr:`SlicePlot.color_by` attribute::
plot.color_by = 'material'
@ -68,8 +68,8 @@ particular cells/materials should be given colors of your choosing::
Note that colors can be given as RGB tuples or by a string indicating a valid
`SVG color <https://www.w3.org/TR/SVG11/types.html#ColorKeywords>`_.
When you're done creating your :class:`openmc.Plot` instances, you need to then
assign them to a :class:`openmc.Plots` collection and export it to XML::
When you're done creating your :class:`openmc.SlicePlot` instances, you need to
then assign them to a :class:`openmc.Plots` collection and export it to XML::
plots = openmc.Plots([plot1, plot2, plot3])
plots.export_to_xml()
@ -97,13 +97,11 @@ Voxel Plots
.. image:: ../_images/3dba.png
:width: 200px
The :class:`openmc.Plot` class can also be told to generate a 3D voxel plot
instead of a 2D slice plot. Simply change the :attr:`Plot.type` attribute to
'voxel'. In this case, the :attr:`Plot.width` and :attr:`Plot.pixels` attributes
should be three items long, e.g.::
The :class:`openmc.VoxelPlot` class enables the generation of a 3D voxel plot
instead of a 2D slice plot. In this case, the :attr:`VoxelPlot.width` and
:attr:`VoxelPlot.pixels` attributes should be three items long, e.g.::
vox_plot = openmc.Plot()
vox_plot.type = 'voxel'
vox_plot = openmc.VoxelPlot()
vox_plot.width = (100., 100., 50.)
vox_plot.pixels = (400, 400, 200)

View file

@ -97,7 +97,15 @@ VTK Mesh File Generation
------------------------
VTK files of OpenMC meshes can be created using the
:meth:`openmc.Mesh.write_data_to_vtk` method. Data can be applied to the
:meth:`openmc.Mesh.write_data_to_vtk` method. This method supports several VTK
formats depending on the mesh type. Structured meshes
(:class:`~openmc.RegularMesh`, :class:`~openmc.RectilinearMesh`,
:class:`~openmc.CylindricalMesh`, and :class:`~openmc.SphericalMesh`) can be
exported to legacy VTK format (``.vtk``). The :class:`~openmc.UnstructuredMesh`
class supports VTK unstructured grid formats (``.vtu``) as well as an HDF5-based
format (``.vtkhdf``) that does not require the ``vtk`` module to write.
Data can be applied to the
elements of the resulting mesh from mesh filter objects. This data can be
provided either as a flat array or, in the case of structured meshes
(:class:`~openmc.RegularMesh`, :class:`~openmc.RectilinearMesh`,

View file

@ -513,6 +513,7 @@ Supported scores:
- total
- fission
- nu-fission
- kappa-fission
- events
Supported Estimators:
@ -644,7 +645,10 @@ model to use these multigroup cross sections. An example is given below::
nparticles=2000,
overwrite_mgxs_library=False,
mgxs_path="mgxs.h5",
correction=None
correction=None,
source_energy=None,
temperatures=None,
temperature_settings=None
)
The most important parameter to set is the ``method`` parameter, which can be
@ -706,6 +710,45 @@ generation and use an existing library file.
with a :math:`\rho` default value of 1.0, which can be adjusted with the
``settings.random_ray['diagonal_stabilization_rho']`` parameter.
When generating MGXS data with either the ``stochastic_slab`` or
``infinite_medium`` methods, by default the simulation will use a uniform source
distribution spread evenly over all energy groups. This ensures that all energy
groups receive tallies and therefore produce non-zero total multigroup cross
sections. Additionally, the function will convert any sources in the model into
simplified spatial sources that retain the original energy distributions. If
sources are present, they will be used 99% of the time to sample source energies
during MGXS generation. The other 1% of the time, energies will be sampled
uniformly over all energy groups to ensure that all groups receive some tallies.
However, the user may wish to specify a different source energy spectrum (for
instance, if they are using a FileSource, such that the energy distribution
cannot be extracted from the python source object). This can be done by
providing a :class:`openmc.stats.Univariate` distribution as the
``source_energy`` parameter of the :meth:`openmc.Model.convert_to_multigroup`
method. If provided, it will override any sources present in the model and will
be used 99% of the time to sample source energies during MGXS generation. The
other 1% of the time, energies will be sampled uniformly over all energy groups
to ensure that all groups receive some tallies.
For instance, a D-D fusion simulation may involve a complex file source. In this
case, the user may wish to provide a discrete 2.45 MeV energy source
distribution for MGXS generation as::
source_energy = openmc.stats.delta_function(2.45e6)
The ``temperatures`` parameter can be provided if temperature-dependent
multi-group cross sections are desired for multi-physics simulations. An
individual cross section generation calculation is run for each temperature
provided, where the materials in the model are set to the temperature. The
temperature settings used during cross section generation can be specified with the
``temperature_settings`` parameter. If no ``temperature_settings`` are provided,
the settings contained in the model will be used. The valid keys and values in the
``temperature_settings`` dictionary are identical to
:attr:`openmc.Settings.temperature_settings`; more information can be found in
:class:`openmc.Settings` . This approach yields isothermal cross section interpolation
tables, which can be inaccurate for systems with large differences between temperatures
in each material (often the case in fission reactors). If a more sophisticated
temperature-dependence is required, we recommend generating cross sections manually.
Ultimately, the methods described above are all just approximations.
Approximations in the generated MGXS data will fundamentally limit the potential
accuracy of the random ray solver. However, the methods described above are all
@ -901,6 +944,8 @@ as::
which will greatly improve the quality of the linear source term in 2D
simulations.
.. _usersguide_random_ray_run_modes:
---------------------------------
Fixed Source and Eigenvalue Modes
---------------------------------
@ -1030,22 +1075,52 @@ The adjoint flux random ray solver mode can be enabled as::
settings.random_ray['adjoint'] = True
When enabled, OpenMC will first run a forward transport simulation followed by
an adjoint transport simulation. The purpose of the forward solve is to compute
the adjoint external source when an external source is present in the
simulation. Simulation settings (e.g., number of rays, batches, etc.) will be
identical for both simulations. At the conclusion of the run, all results (e.g.,
tallies, plots, etc.) will be derived from the adjoint flux rather than the
forward flux but are not labeled any differently. The initial forward flux
solution will not be stored or available in the final statepoint file. Those
wishing to do analysis requiring both the forward and adjoint solutions will
need to run two separate simulations and load both statepoint files.
When enabled, OpenMC will first run a forward transport simulation if there are
no user-specified adjoint sources present, followed by an adjoint transport
simulation. Fixed adjoint sources can be specified on the
:attr:`openmc.Settings.random_ray` dictionary as follows::
# Geometry definition
...
detector_cell = openmc.Cell(fill=detector_mat, name='cell where detector will be')
...
# Define fixed adjoint neutron source
strengths = [1.0]
midpoints = [1.0e-4]
energy_distribution = openmc.stats.Discrete(x=midpoints, p=strengths)
adj_source = openmc.IndependentSource(
energy=energy_distribution,
constraints={'domains': [detector_cell]}
)
# Add to random_ray dict
settings.random_ray['adjoint_source'] = adj_source
The same constraints apply to the user-defined adjoint source as to the forward
source, described in the :ref:`Fixed Source and Eigenvalue section
<usersguide_random_ray_run_modes>`. If this source is not provided, a forward
solve must take place to compute the adjoint external source when a forward
external source is present in the problem. Simulation settings (e.g., number of
rays, batches, etc.) will be identical for both calculations. At the
conclusion of the run, all results (e.g., tallies, plots, etc.) will be
derived from the adjoint flux rather than the forward flux but are not labeled
any differently. When an initial forward solve is performed (i.e., when no
user-specified adjoint source is present), its output files are also written to
disk with a ``forward`` infix, so they are not overwritten by the subsequent
adjoint solve. This applies to the statepoint, ``tallies.out``, and any voxel
plots, e.g., ``statepoint.forward.N.h5`` and ``tallies.forward.out``; the
adjoint solve keeps the usual file names. This allows analyses requiring both
the forward and adjoint solutions to be performed from a single run. When
generating FW-CADIS weight windows, no weight window file is written for the
forward solve, as only the final adjoint-derived weight windows are meaningful.
.. note::
When adjoint mode is selected, OpenMC will always perform a full forward
solve and then run a full adjoint solve immediately afterwards. Statepoint
and tally results will be derived from the adjoint flux, but will not be
labeled any differently.
Use of the automated
:ref:`FW-CADIS weight window generator<usersguide_fw_cadis>` is not
currently compatible with user-defined adjoint sources. Instead, the
initial forward calculation is used to assign "forward-weighted" adjoint
sources to the tally regions of interest.
---------------------------------------
Putting it All Together: Example Inputs
@ -1105,11 +1180,10 @@ given below:
tallies.export_to_xml()
# Create voxel plot
plot = openmc.Plot()
plot = openmc.VoxelPlot()
plot.origin = [0, 0, 0]
plot.width = [2*pitch, 2*pitch, 1]
plot.pixels = [1000, 1000, 1]
plot.type = 'voxel'
# Instantiate a Plots collection and export to XML
plots = openmc.Plots([plot])
@ -1189,11 +1263,10 @@ given below:
tallies.export_to_xml()
# Create voxel plot
plot = openmc.Plot()
plot = openmc.VoxelPlot()
plot.origin = [0, 0, 0]
plot.width = [2*pitch, 2*pitch, 1]
plot.pixels = [1000, 1000, 1]
plot.type = 'voxel'
# Instantiate a Plots collection and export to XML
plots = openmc.Plots([plot])

View file

@ -48,6 +48,7 @@ flags:
restart file
-s, --threads N Run with *N* OpenMP threads
-t, --track Write tracks for all particles (up to max_tracks)
-q, --verbosity V Set the output verbosity to *V*
-v, --version Show version information
-h, --help Show help message

View file

@ -272,6 +272,12 @@ option::
settings.source = [src1, src2]
settings.uniform_source_sampling = True
Additionally, sampling from an :class:`openmc.IndependentSource` may be biased
for local or global variance reduction by modifying the
:attr:`~openmc.IndependentSource.bias` attribute of each of its four main
distributions. Further discussion of source biasing can be found in
:ref:`source_biasing`.
Finally, the :attr:`IndependentSource.particle` attribute can be used to
indicate the source should be composed of particles other than neutrons. For
example, the following would generate a photon source::
@ -285,6 +291,53 @@ example, the following would generate a photon source::
For a full list of all classes related to statistical distributions, see
:ref:`pythonapi_stats`.
Tokamak Plasma Sources
----------------------
For fusion applications, the :class:`openmc.TokamakSource` class provides a
native parametric neutron source for tokamak plasmas. Rather than specifying
spatial, angular, and energy distributions separately, the source is defined by
the plasma geometry (using a `Miller-style flux-surface parameterization
<https://doi.org/10.1063/1.872666>`_) and a radial emission profile. Source
sites are sampled directly from the plasma volume without rejection.
The plasma shape is described by the major radius :math:`R_0`, minor radius
:math:`a`, elongation :math:`\kappa`, triangularity :math:`\delta`, and
Shafranov shift :math:`\Delta`. The neutron birth profile is given as an
emission density :math:`S(r/a)` tabulated on a normalized minor-radius grid that
runs from 0 (magnetic axis) to 1 (last closed flux surface); only the shape of
the profile matters, since it is normalized internally. The emission density is
linearly interpolated between the supplied points and refined internally for
radial sampling. For example::
import numpy as np
r_over_a = np.linspace(0.0, 1.0, 50)
emission = (1.0 - r_over_a**2)**2 # peaked on-axis profile
source = openmc.TokamakSource(
major_radius=620.0, # cm
minor_radius=200.0, # cm
elongation=1.8,
triangularity=0.45,
shafranov_shift=10.0, # cm
r_over_a=r_over_a,
emission_density=emission,
energy=openmc.stats.muir(e0=14.08e6, m_rat=5.0, kt=20000.0),
)
settings.source = source
The ``energy`` argument accepts either a single
:class:`~openmc.stats.Univariate` distribution applied at all radii, or a
sequence with one distribution per ``r_over_a`` grid point to model a
radially-varying neutron spectrum (energies are then sampled by stochastic
interpolation between the two distributions bracketing the sampled radius). A
time distribution can be given with the ``time`` argument; by default, particles
are born at :math:`t=0`. The toroidal extent can be restricted with
``phi_start`` and ``phi_extent`` to model a sector of the plasma, and
``vertical_shift`` translates the plasma center along the z-axis.
File-based Sources
------------------
@ -394,7 +447,7 @@ below.
{
openmc::SourceSite particle;
// weight
particle.particle = openmc::ParticleType::neutron;
particle.particle = openmc::ParticleType::neutron();
particle.wgt = 1.0;
// position
double angle = 2.0 * M_PI * openmc::prn(seed);
@ -471,7 +524,7 @@ parameters to the source class when it is created:
{
openmc::SourceSite particle;
// weight
particle.particle = openmc::ParticleType::neutron;
particle.particle = openmc::ParticleType::neutron();
particle.wgt = 1.0;
// position
particle.r.x = 0.0;
@ -598,6 +651,13 @@ transport::
settings.photon_transport = True
Atomic relaxation (the cascade of fluorescence photons and Auger electrons
emitted when an inner-shell vacancy is filled) is enabled by default whenever
photon transport is on. It can be disabled using the
:attr:`Settings.atomic_relaxation` attribute::
settings.atomic_relaxation = False
The way in which OpenMC handles secondary charged particles can be specified
with the :attr:`Settings.electron_treatment` attribute. By default, the
:ref:`thick-target bremsstrahlung <ttb>` (TTB) approximation is used to generate
@ -779,6 +839,11 @@ collision_track.h5 file at the end of the simulation. The file contains
300 recorded collisions that occurred in materials with IDs 1 or 2, involving
fission or (n,2n) reactions on the nuclides U-238 or O-16, within cells
with IDs 5 and 12.
.. note::
Electron and positron collision-track events are not associated with a
specific nuclide. If a ``nuclides`` entry is specified, these events are omitted.
The file can be read using :func:`openmc.read_collision_track_file`.
The example below shows how to extract the data from the collision_track
feature and displays the fields stored in the file:

View file

@ -105,109 +105,124 @@ The following tables show all valid scores:
.. table:: **Reaction scores: units are reactions per source particle.**
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|absorption |Total absorption rate. For incident neutrons, this |
| |accounts for all reactions that do not produce |
| |secondary neutrons as well as fission. For incident|
| |photons, this includes photoelectric and pair |
| |production. |
+----------------------+---------------------------------------------------+
|elastic |Elastic scattering reaction rate. |
+----------------------+---------------------------------------------------+
|fission |Total fission reaction rate. |
+----------------------+---------------------------------------------------+
|scatter |Total scattering rate. |
+----------------------+---------------------------------------------------+
|total |Total reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2nd) |(n,2nd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2n) |(n,2n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3n) |(n,3n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,na) |(n,n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n3a) |(n,n3\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2na) |(n,2n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3na) |(n,3n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,np) |(n,np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n2a) |(n,n2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2n2a) |(n,2n2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nd) |(n,nd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nt) |(n,nt) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n3He) |(n,n\ :sup:`3`\ He) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nd2a) |(n,nd2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nt2a) |(n,nt2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,4n) |(n,4n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2np) |(n,2np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3np) |(n,3np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n2p) |(n,n2p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n*X*) |Level inelastic scattering reaction rate. The *X* |
| |indicates what which inelastic level, e.g., (n,n3) |
| |is third-level inelastic scattering. |
+----------------------+---------------------------------------------------+
|(n,nc) |Continuum level inelastic scattering reaction rate.|
+----------------------+---------------------------------------------------+
|(n,gamma) |Radiative capture reaction rate. |
+----------------------+---------------------------------------------------+
|(n,p) |(n,p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,d) |(n,d) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,t) |(n,t) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3He) |(n,\ :sup:`3`\ He) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,a) |(n,\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2a) |(n,2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3a) |(n,3\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2p) |(n,2p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pa) |(n,p\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,t2a) |(n,t2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,d2a) |(n,d2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pd) |(n,pd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pt) |(n,pt) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,da) |(n,d\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|coherent-scatter |Coherent (Rayleigh) scattering reaction rate. |
+----------------------+---------------------------------------------------+
|incoherent-scatter |Incoherent (Compton) scattering reaction rate. |
+----------------------+---------------------------------------------------+
|photoelectric |Photoelectric absorption reaction rate. |
+----------------------+---------------------------------------------------+
|pair-production |Pair production reaction rate. |
+----------------------+---------------------------------------------------+
|*Arbitrary integer* |An arbitrary integer is interpreted to mean the |
| |reaction rate for a reaction with a given ENDF MT |
| |number. |
+----------------------+---------------------------------------------------+
+------------------------+-------------------------------------------------+
|Score |Description |
+========================+=================================================+
|absorption |Total absorption rate. For incident neutrons, |
| |this accounts for all reactions that do not |
| |produce secondary neutrons as well as fission. |
| |For incident photons, this includes |
| |photoelectric and pair production. |
+------------------------+-------------------------------------------------+
|elastic |Elastic scattering reaction rate. |
+------------------------+-------------------------------------------------+
|fission |Total fission reaction rate. |
+------------------------+-------------------------------------------------+
|scatter |Total scattering rate. |
+------------------------+-------------------------------------------------+
|total |Total reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2nd) |(n,2nd) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2n) |(n,2n) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,3n) |(n,3n) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,na) |(n,n\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,n3a) |(n,n3\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2na) |(n,2n\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,3na) |(n,3n\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,np) |(n,np) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,n2a) |(n,n2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2n2a) |(n,2n2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,nd) |(n,nd) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,nt) |(n,nt) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,n3He) |(n,n\ :sup:`3`\ He) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,nd2a) |(n,nd2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,nt2a) |(n,nt2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,4n) |(n,4n) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2np) |(n,2np) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,3np) |(n,3np) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,n2p) |(n,n2p) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,npa) |(n,np\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,n*X*) |Level inelastic scattering reaction rate. The |
| |*X* indicates which inelastic level, e.g., |
| |(n,n3) is third-level inelastic scattering. |
+------------------------+-------------------------------------------------+
|(n,nc) |Continuum level inelastic scattering |
| |reaction rate. |
+------------------------+-------------------------------------------------+
|(n,gamma) |Radiative capture reaction rate. |
+------------------------+-------------------------------------------------+
|(n,p) |(n,p) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,d) |(n,d) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,t) |(n,t) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,3He) |(n,\ :sup:`3`\ He) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,a) |(n,\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2a) |(n,2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,3a) |(n,3\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,2p) |(n,2p) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,pa) |(n,p\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,t2a) |(n,t2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,d2a) |(n,d2\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,pd) |(n,pd) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,pt) |(n,pt) reaction rate. |
+------------------------+-------------------------------------------------+
|(n,da) |(n,d\ :math:`\alpha`\ ) reaction rate. |
+------------------------+-------------------------------------------------+
|photon-total |Total photo-atomic reaction rate. |
+------------------------+-------------------------------------------------+
|coherent-scatter |Coherent (Rayleigh) scattering reaction rate. |
+------------------------+-------------------------------------------------+
|incoherent-scatter |Incoherent (Compton) scattering reaction rate. |
+------------------------+-------------------------------------------------+
|photoelectric |Photoelectric absorption reaction rate. |
+------------------------+-------------------------------------------------+
|photoelectric-*S* |Subshell photoelectric absorption rate for the |
| |*S* shell. For example, "photoelectric-N3" is the|
| |rate for the N3 subshell. |
+------------------------+-------------------------------------------------+
|pair-production |Pair production reaction rate (total). |
+------------------------+-------------------------------------------------+
|pair-production-electron|Pair production reaction rate in the electron |
| |field. |
+------------------------+-------------------------------------------------+
|pair-production-nuclear |Pair production reaction rate in the nuclear |
| |field. |
+------------------------+-------------------------------------------------+
|*Arbitrary integer* |An arbitrary integer is interpreted to mean the |
| |reaction rate for a reaction with a given ENDF |
| |MT number. |
+------------------------+-------------------------------------------------+
.. table:: **Particle production scores: units are particles produced per
source particles.**
@ -246,18 +261,21 @@ The following tables show all valid scores:
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|current |Used in combination with a meshsurface filter: |
|current |It may not be used in conjunction with any other |
| |score except flux. |
| | |
| |When used in combination with a meshsurface filter:|
| |Partial currents on the boundaries of each cell in |
| |a mesh. It may not be used in conjunction with any |
| |other score. Only energy and mesh filters may be |
| |used. |
| |Used in combination with a surface filter: |
| |a mesh. |
| | |
| |When used in combination with a surface filter: |
| |Net currents on any surface previously defined in |
| |the geometry. It may be used along with any other |
| |filter, except meshsurface filters. |
| |Surfaces can alternatively be defined with cell |
| |from and cell filters thereby resulting in tallying|
| |partial currents. |
| | |
| |Units are particles per source particle. |
+----------------------+---------------------------------------------------+
|events |Number of scoring events. Units are events per |

View file

@ -4,24 +4,27 @@
Variance Reduction
==================
Global variance reduction in OpenMC is accomplished by weight windowing
techniques. OpenMC is capable of generating weight windows using either the
MAGIC or FW-CADIS methods. Both techniques will produce a ``weight_windows.h5``
file that can be loaded and used later on. In this section, we break down the
steps required to both generate and then apply weight windows.
Global and local variance reduction are possible in OpenMC through both weight
windowing and source biasing techniques. OpenMC is capable of generating weight
windows using either the MAGIC or FW-CADIS methods, the latter with an optional
capability for local variance reduction. Both techniques will produce a
``weight_windows.h5`` file that can be loaded and used later on. In
this section, we first break down the steps required to generate and apply
weight windows, then describe how source biasing may be applied.
.. _ww_generator:
------------------------------------
Generating Weight Windows with MAGIC
------------------------------------
-------------------------------------------
Generating Global Weight Windows with MAGIC
-------------------------------------------
As discussed in the :ref:`methods section <methods_variance_reduction>`, MAGIC
is an iterative method that uses flux tally information from a Monte Carlo
simulation to produce weight windows for a user-defined mesh. While generating
the weight windows, OpenMC is capable of applying the weight windows generated
from a previous batch while processing the next batch, allowing for progressive
improvement in the weight window quality across iterations.
simulation to produce weight windows for a user-defined mesh with the objective
of global variance reduction. While generating the weight windows, OpenMC is
capable of applying the weight windows generated from a previous batch while
processing the next batch, allowing for progressive improvement in the weight
window quality across iterations.
The typical way of generating weight windows is to define a mesh and then add an
:class:`openmc.WeightWindowGenerator` object to an :attr:`openmc.Settings`
@ -69,15 +72,20 @@ At the end of the simulation, a ``weight_windows.h5`` file will be saved to disk
for later use. Loading it in another subsequent simulation will be discussed in
the "Using Weight Windows" section below.
------------------------------------------------------
Generating Weight Windows with FW-CADIS and Random Ray
------------------------------------------------------
.. _usersguide_fw_cadis:
----------------------------------------------------------------------
Generating Global or Local Weight Windows with FW-CADIS and Random Ray
----------------------------------------------------------------------
Weight window generation with FW-CADIS and random ray in OpenMC uses the same
exact strategy as with MAGIC. An :class:`openmc.WeightWindowGenerator` object is
added to the :attr:`openmc.Settings` object, and a ``weight_windows.h5`` will be
generated at the end of the simulation. The only difference is that the code
must be run in random ray mode. A full description of how to enable and setup
exact strategy as with MAGIC. Using FW-CADIS, however, also enables
local variance reduction in fixed source problems through the :attr:`targets`
attribute, which is described later in this section. To enable FW-CADIS, an
:class:`openmc.WeightWindowGenerator` object is added to the
:attr:`openmc.Settings` object, and a ``weight_windows.h5`` will be generated
at the end of the simulation. The only procedural difference is that the code
must be run in random ray mode. A full description of how to enable and setup
random ray mode can be found in the :ref:`Random Ray User Guide <random_ray>`.
.. note::
@ -88,7 +96,7 @@ random ray mode can be found in the :ref:`Random Ray User Guide <random_ray>`.
ray solver. A high level overview of the current workflow for generation of
weight windows with FW-CADIS using random ray is given below.
1. Begin by making a deepy copy of your continuous energy Python model and then
1. Begin by making a deep copy of your continuous energy Python model and then
convert the copy to be multigroup and use the random ray transport solver.
The conversion process can largely be automated as described in more detail
in the :ref:`random ray quick start guide <quick_start>`, summarized below::
@ -146,7 +154,53 @@ random ray mode can be found in the :ref:`Random Ray User Guide <random_ray>`.
assigning to ``model.settings.random_ray['source_region_meshes']``) and for
weight window generation.
3. When running your multigroup random ray input deck, OpenMC will automatically
3. (Optional) If local variance reduction is desired in a fixed-source problem,
populate the :attr:`targets` attribute with an :class:`openmc.Tallies`
instance or an iterable of tally IDs indicating the tallies of interest for
variance reduction::
# Build a new example and WWG for local variance reduction
from openmc.examples import random_ray_three_region_cube_with_detectors
new_model = random_ray_three_region_cube_with_detectors()
ww_mesh = openmc.RegularMesh()
n = 7
width = 35.0
ww_mesh.dimension = (n, n, n)
ww_mesh.lower_left = (0.0, 0.0, 0.0)
ww_mesh.upper_right = (width, width, width)
wwg = openmc.WeightWindowGenerator(
method="fw_cadis",
mesh=ww_mesh,
max_realizations=new_model.settings.batches
)
new_model.settings.weight_window_generators = wwg
new_model.settings.random_ray['volume_estimator'] = 'naive'
# Get the tallies of interest
target_tallies = openmc.Tallies()
for tally in list(new_model.tallies):
if tally.name in {"Detector 1 Tally", "Detector 2 Tally"}:
target_tallies.append(tally)
# Add to WeightWindowGenerator
wwg.targets = target_tallies
.. warning::
The tallies designated as FW-CADIS targets to the
:class:`~openmc.WeightWindowGenerator` must be present under the
:class:`~openmc.model.Model.tallies` attribute of the
:class:`~openmc.model.Model` as well in order to be recognized as valid
local variance reduction targets. This check is performed when the
:func:`openmc.model.Model.export_to_model_xml` or
:func:`openmc.model.Model.export_to_xml` functions are called, meaning
that the standalone :func:`openmc.Settings.export_to_xml` and
:func:`openmc.Tallies.export_to_xml` methods should not be used with
FW-CADIS local variance reduction.
4. When running your multigroup random ray input deck, OpenMC will automatically
run a forward solve followed by an adjoint solve, with a
``weight_windows.h5`` file generated at the end. The ``weight_windows.h5``
file will contain FW-CADIS generated weight windows. This file can be used in
@ -172,3 +226,148 @@ Weight window mesh information is embedded into the weight window file, so the
mesh does not need to be redefined. Monte Carlo solves that load a weight window
file as above will utilize weight windows to reduce the variance of the
simulation.
.. _source_biasing:
--------------
Source Biasing
--------------
In fixed source problems, source biasing provides a means to reduce the variance
on global or localized responses, depending on the biasing scheme. In either
case, the premise of the method is to sample source sites from a biased
distribution that directs a larger fraction of the simulated histories towards
phase space regions of interest than would be found there under analog sampling.
In order to preserve an unbiased estimate of the tally mean, the weight of these
with analog sampling, divided by the probability assigned by the biased
distribution. While the assignment of statistical weights is outlined in the
:ref:`methods section <methods_source_biasing>`, this section demonstrates the
implementation of source biasing to problems in OpenMC.
Source biasing in OpenMC is accomplished by applying a distribution to the
:attr:`bias` attribute of one or more of the univariate or independent
multivariate distributions which make up an :class:`~openmc.IndependentSource`
instance as follows::
# First create the biased distribution
biased_dist = openmc.stats.PowerLaw(a=0, b=3, n=3)
# Construct a new distribution with the bias applied
dist = openmc.stats.PowerLaw(a=0, b=3, n=2, bias=biased_dist)
# The bias attribute can also be set on an existing "analog" distribution:
sphere_dist = openmc.stats.spherical_uniform(r_outer=3)
sphere_dist.r.bias = biased_dist
Univariate distributions may be sampled via the Python API, returning the
sample(s) along with the associated weight(s)::
sample_vec, wgt_vec = dist.sample(n_samples=100)
Here, if the distribution is unbiased, the weight of each sample will be unity.
Finally, :class:`~openmc.IndependentSource` instances can be constructed with
biased distributions::
# Create a source with a biased spatial distribution
source = openmc.IndependentSource(space=sphere_dist)
During the simulation, source sites are then sampled using the biased
distributions where available and given starting statistical weights
corresponding to the cumulative product of the weights assigned by each
distribution in the source object. Hence multiple source variables (e.g.,
direction and energy) may be biased and the resulting source sites will have
their weights adjusted accordingly.
.. note::
Combining source biasing with weight windows can be a powerful variance
reduction technique if each is constructed appropriately for the response
of interest. For example, if a source biasing scheme is devised for
variance reduction of a specific localized response, the user may be able
to specify their own weight window structure that results in more efficient
transport than if weight windows were generated by either of OpenMC's
automatic weight window generators, which are intended for global variance
reduction.
Biased distributions that could result in degenerate weight mappings are not
recommended; this is most commonly seen when biasing the :math:`\phi`-coordinate
of spherical or cylindrical independent multivariate distributions. In such
cases degenerate behavior will be observed at the pole about which :math:`\phi`
is measured, with all values of :math:`\phi` (hence many possible statistical
weights) mapping to the same point for :math:`r=0` or :math:`\mu=0`, and large
weight gradients in the vicinity. In most cases requiring a spherical
independent source, it would be preferable to reorient the reference vector of
the distribution such that biasing could be applied to the
:math:`\mu`-coordinate instead.
When biasing a distribution, care should also be taken to ensure that both the
unbiased and biased distribution share a common support---that is, every region
of phase space mapped to a nonzero probability density by the unbiased
distribution should likewise map to nonzero probability under the biased
distribution, and vice versa. In OpenMC, this places restrictions on the set of
compatible distributions that may be used to bias sampling of each distribution
type. The following table summarizes the method for each distribution in OpenMC
that permits biased sampling.
.. list-table:: **Distributions that support biased sampling**
:header-rows: 1
:widths: 35 65
* - Discrete Univariate PDFs
- Biasing Method
* - :class:`openmc.stats.Discrete`
- Apply a vector of alternative probabilities to the :attr:`bias`
attribute
.. list-table::
:header-rows: 1
:widths: 35 65
* - Continuous Univariate PDFs
- Biasing Method
* - :class:`openmc.stats.Uniform`,
:class:`openmc.stats.PowerLaw`,
:class:`openmc.stats.Maxwell`,
:class:`openmc.stats.Watt`,
:class:`openmc.stats.Normal`,
:class:`openmc.stats.Tabular`
- Apply a second, unbiased continous univariate PDF to the :attr:`bias`
attribute, ensuring that the :attr:`support` attribute of each
distribution is the same
.. list-table::
:header-rows: 1
:widths: 35 65
* - Mixed Univariate PDFs
- Biasing Method
* - :class:`openmc.stats.Mixture`
- May be constructed from multiple biased univariate distributions, or a
second, unbiased continous univariate PDF may be applied to the
:attr:`bias` attribute
.. list-table::
:header-rows: 1
:widths: 35 65
* - Discrete Multivariate PDFs
- Biasing Method
* - :class:`openmc.stats.PointCloud`,
:class:`openmc.stats.MeshSpatial`
- Apply a vector of the new relative probabilities of each point or mesh
element under biased sampling to the :attr:`bias` attribute
.. list-table::
:header-rows: 1
:widths: 35 65
* - Continuous Multivariate PDFs
- Biasing Method
* - :class:`openmc.stats.CartesianIndependent`,
:class:`openmc.stats.CylindricalIndependent`,
:class:`openmc.stats.SphericalIndependent`,
:class:`openmc.stats.PolarAzimuthal`
- Construct from biased univariate distributions for :attr:`x`, :attr:`y`,
:attr:`z`, etc.
* - :class:`openmc.stats.Isotropic`
- Apply an unbiased :class:`openmc.stats.PolarAzimuthal` to the
:attr:`bias` attribute

View file

@ -1,17 +1,17 @@
#include <cmath> // for M_PI
#define _USE_MATH_DEFINES
#include <cmath> // for M_PI
#include <memory> // for unique_ptr
#include "openmc/particle.h"
#include "openmc/random_lcg.h"
#include "openmc/source.h"
#include "openmc/particle.h"
class RingSource : public openmc::Source
{
class RingSource : public openmc::Source {
openmc::SourceSite sample(uint64_t* seed) const
{
openmc::SourceSite particle;
// particle type
particle.particle = openmc::ParticleType::neutron;
particle.particle = openmc::ParticleType::neutron();
// position
double angle = 2.0 * M_PI * openmc::prn(seed);
double radius = 3.0;
@ -25,10 +25,11 @@ class RingSource : public openmc::Source
}
};
// A function to create a unique pointer to an instance of this class when generated
// via a plugin call using dlopen/dlsym.
// You must have external C linkage here otherwise dlopen will not find the file
extern "C" std::unique_ptr<RingSource> openmc_create_source(std::string parameters)
// A function to create a unique pointer to an instance of this class when
// generated via a plugin call using dlopen/dlsym. You must have external C
// linkage here otherwise dlopen will not find the file
extern "C" std::unique_ptr<RingSource> openmc_create_source(
std::string parameters)
{
return std::make_unique<RingSource>();
}

View file

@ -128,14 +128,14 @@ settings_file.export_to_xml()
# Exporting to OpenMC plots.xml file
###############################################################################
plot_xy = openmc.Plot(plot_id=1)
plot_xy = openmc.SlicePlot(plot_id=1)
plot_xy.filename = 'plot_xy'
plot_xy.origin = [0, 0, 0]
plot_xy.width = [6, 6]
plot_xy.pixels = [400, 400]
plot_xy.color_by = 'material'
plot_yz = openmc.Plot(plot_id=2)
plot_yz = openmc.SlicePlot(plot_id=2)
plot_yz.filename = 'plot_yz'
plot_yz.basis = 'yz'
plot_yz.origin = [0, 0, 0]

View file

@ -135,7 +135,7 @@ settings_file.export_to_xml()
# Exporting to OpenMC plots.xml file
###############################################################################
plot = openmc.Plot(plot_id=1)
plot = openmc.SlicePlot(plot_id=1)
plot.origin = [0, 0, 0]
plot.width = [4, 4]
plot.pixels = [400, 400]

View file

@ -128,7 +128,7 @@ settings_file.export_to_xml()
# Exporting to OpenMC plots.xml file
###############################################################################
plot = openmc.Plot(plot_id=1)
plot = openmc.SlicePlot(plot_id=1)
plot.origin = [0, 0, 0]
plot.width = [4, 4]
plot.pixels = [400, 400]

View file

@ -1,63 +1,66 @@
#include <cmath> // for M_PI
#include <memory> // for unique_ptr
#define _USE_MATH_DEFINES
#include <cmath>
#include <memory>
#include <unordered_map>
#include "openmc/particle.h"
#include "openmc/random_lcg.h"
#include "openmc/source.h"
#include "openmc/particle.h"
class RingSource : public openmc::Source {
public:
RingSource(double radius, double energy) : radius_(radius), energy_(energy) { }
public:
RingSource(double radius, double energy) : radius_(radius), energy_(energy) {}
// Defines a function that can create a unique pointer to a new instance of this class
// by extracting the parameters from the provided string.
static std::unique_ptr<RingSource> from_string(std::string parameters)
{
std::unordered_map<std::string, std::string> parameter_mapping;
// Defines a function that can create a unique pointer to a new instance of
// this class by extracting the parameters from the provided string.
static std::unique_ptr<RingSource> from_string(std::string parameters)
{
std::unordered_map<std::string, std::string> parameter_mapping;
std::stringstream ss(parameters);
std::string parameter;
while (std::getline(ss, parameter, ',')) {
parameter.erase(0, parameter.find_first_not_of(' '));
std::string key = parameter.substr(0, parameter.find_first_of('='));
std::string value = parameter.substr(parameter.find_first_of('=') + 1, parameter.length());
parameter_mapping[key] = value;
}
double radius = std::stod(parameter_mapping["radius"]);
double energy = std::stod(parameter_mapping["energy"]);
return std::make_unique<RingSource>(radius, energy);
std::stringstream ss(parameters);
std::string parameter;
while (std::getline(ss, parameter, ',')) {
parameter.erase(0, parameter.find_first_not_of(' '));
std::string key = parameter.substr(0, parameter.find_first_of('='));
std::string value =
parameter.substr(parameter.find_first_of('=') + 1, parameter.length());
parameter_mapping[key] = value;
}
// Samples from an instance of this class.
openmc::SourceSite sample(uint64_t* seed) const
{
openmc::SourceSite particle;
// particle type
particle.particle = openmc::ParticleType::neutron;
// position
double angle = 2.0 * M_PI * openmc::prn(seed);
double radius = this->radius_;
particle.r.x = radius * std::cos(angle);
particle.r.y = radius * std::sin(angle);
particle.r.z = 0.0;
// angle
particle.u = {1.0, 0.0, 0.0};
particle.E = this->energy_;
double radius = std::stod(parameter_mapping["radius"]);
double energy = std::stod(parameter_mapping["energy"]);
return std::make_unique<RingSource>(radius, energy);
}
return particle;
}
// Samples from an instance of this class.
openmc::SourceSite sample(uint64_t* seed) const
{
openmc::SourceSite particle;
// particle type
particle.particle = openmc::ParticleType::neutron();
// position
double angle = 2.0 * M_PI * openmc::prn(seed);
double radius = this->radius_;
particle.r.x = radius * std::cos(angle);
particle.r.y = radius * std::sin(angle);
particle.r.z = 0.0;
// angle
particle.u = {1.0, 0.0, 0.0};
particle.E = this->energy_;
private:
double radius_;
double energy_;
return particle;
}
private:
double radius_;
double energy_;
};
// A function to create a unique pointer to an instance of this class when generated
// via a plugin call using dlopen/dlsym.
// You must have external C linkage here otherwise dlopen will not find the file
extern "C" std::unique_ptr<RingSource> openmc_create_source(std::string parameters)
// A function to create a unique pointer to an instance of this class when
// generated via a plugin call using dlopen/dlsym. You must have external C
// linkage here otherwise dlopen will not find the file
extern "C" std::unique_ptr<RingSource> openmc_create_source(
std::string parameters)
{
return RingSource::from_string(parameters);
}

View file

@ -192,11 +192,10 @@ tallies.export_to_xml()
# Exporting to OpenMC plots.xml file
###############################################################################
plot = openmc.Plot()
plot = openmc.VoxelPlot()
plot.origin = [0, 0, 0]
plot.width = [pitch, pitch, pitch]
plot.pixels = [1000, 1000, 1]
plot.type = 'voxel'
# Instantiate a Plots collection and export to XML
plots = openmc.Plots([plot])

View file

@ -14,8 +14,22 @@ namespace openmc {
class AngleEnergy {
public:
//! Sample an outgoing energy and scattering cosine
//! \param[in] E_in Incoming energy in [eV]
//! \param[out] E_out Outgoing energy in [eV]
//! \param[out] mu Outgoing cosine with respect to current direction
//! \param[inout] seed Pseudorandom seed pointer
virtual void sample(
double E_in, double& E_out, double& mu, uint64_t* seed) const = 0;
//! Sample an outgoing energy and evaluate the angular PDF
//! \param[in] E_in Incoming energy in [eV]
//! \param[in] mu Scattering cosine with respect to current direction
//! \param[out] E_out Outgoing energy in [eV]
//! \param[inout] seed Pseudorandom seed pointer
//! \return Probability density for the scattering cosine
virtual double sample_energy_and_pdf(
double E_in, double mu, double& E_out, uint64_t* seed) const = 0;
virtual ~AngleEnergy() = default;
};

View file

@ -0,0 +1,28 @@
//==============================================================================
// atomic masses definitions
//==============================================================================
#ifndef OPENMC_ATOMIC_MASS_H
#define OPENMC_ATOMIC_MASS_H
#include <cstdint>
#include <unordered_map>
namespace openmc {
// Values here are from the Committee on Data for Science and Technology
// (CODATA) 2018 recommendation (https://physics.nist.gov/cuu/Constants/).
// Physical constants
constexpr double MASS_ELECTRON {5.48579909065e-4}; // mass of an electron in amu
constexpr double MASS_NEUTRON {1.00866491595}; // mass of a neutron in amu
constexpr double MASS_PROTON {1.007276466621}; // mass of a proton in amu
constexpr double MASS_DEUTRON {2.013553212745}; // mass of a deutron in amu
constexpr double MASS_HELION {3.014932247175}; // mass of a helion in amu
constexpr double MASS_ALPHA {4.001506179127}; // mass of an alpha in amu
extern std::unordered_map<int32_t, double> ATOMIC_MASS;
} // namespace openmc
#endif // OPENMC_ATOMIC_MASS_H

View file

@ -34,18 +34,24 @@ extern vector<vector<double>> ifp_fission_lifetime_bank;
extern vector<int64_t> progeny_per_particle;
extern SharedArray<SourceSite> shared_secondary_bank_read;
extern SharedArray<SourceSite> shared_secondary_bank_write;
} // namespace simulation
//==============================================================================
// Non-member functions
//==============================================================================
void sort_fission_bank();
void sort_bank(SharedArray<SourceSite>& bank, bool is_fission_bank);
void free_memory_bank();
void init_fission_bank(int64_t max);
int64_t synchronize_global_secondary_bank(
SharedArray<SourceSite>& shared_secondary_bank);
} // namespace openmc
#endif // OPENMC_BANK_H

View file

@ -16,8 +16,9 @@
namespace openmc {
template<typename SiteType>
void write_bank_dataset(const char* dataset_name, hid_t group_id,
span<SiteType> bank, const vector<int64_t>& bank_index, hid_t banktype
void write_bank_dataset(
const char* dataset_name, hid_t group_id, span<SiteType> bank,
const vector<int64_t>& bank_index, hid_t membanktype, hid_t filebanktype
#ifdef OPENMC_MPI
,
MPI_Datatype mpi_dtype
@ -30,8 +31,8 @@ void write_bank_dataset(const char* dataset_name, hid_t group_id,
#ifdef PHDF5
hsize_t dims[] {static_cast<hsize_t>(dims_size)};
hid_t dspace = H5Screate_simple(1, dims, nullptr);
hid_t dset = H5Dcreate(group_id, dataset_name, banktype, dspace, H5P_DEFAULT,
H5P_DEFAULT, H5P_DEFAULT);
hid_t dset = H5Dcreate(group_id, dataset_name, filebanktype, dspace,
H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);
hsize_t count[] {static_cast<hsize_t>(count_size)};
hid_t memspace = H5Screate_simple(1, count, nullptr);
@ -42,7 +43,7 @@ void write_bank_dataset(const char* dataset_name, hid_t group_id,
hid_t plist = H5Pcreate(H5P_DATASET_XFER);
H5Pset_dxpl_mpio(plist, H5FD_MPIO_COLLECTIVE);
H5Dwrite(dset, banktype, memspace, dspace, plist, bank.data());
H5Dwrite(dset, membanktype, memspace, dspace, plist, bank.data());
H5Sclose(dspace);
H5Sclose(memspace);
@ -52,7 +53,7 @@ void write_bank_dataset(const char* dataset_name, hid_t group_id,
if (mpi::master) {
hsize_t dims[] {static_cast<hsize_t>(dims_size)};
hid_t dspace = H5Screate_simple(1, dims, nullptr);
hid_t dset = H5Dcreate(group_id, dataset_name, banktype, dspace,
hid_t dset = H5Dcreate(group_id, dataset_name, filebanktype, dspace,
H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);
#ifdef OPENMC_MPI
@ -75,7 +76,8 @@ void write_bank_dataset(const char* dataset_name, hid_t group_id,
H5Sselect_hyperslab(
dspace_rank, H5S_SELECT_SET, start, nullptr, count, nullptr);
H5Dwrite(dset, banktype, memspace, dspace_rank, H5P_DEFAULT, bank.data());
H5Dwrite(
dset, membanktype, memspace, dspace_rank, H5P_DEFAULT, bank.data());
H5Sclose(memspace);
H5Sclose(dspace_rank);

View file

@ -138,18 +138,28 @@ protected:
//==============================================================================
//! A BC that rotates particles about a global axis.
//
//! Currently only rotations about the z-axis are supported.
//! Only rotations about the x, y, and z axes are supported.
//==============================================================================
class RotationalPeriodicBC : public PeriodicBC {
public:
RotationalPeriodicBC(int i_surf, int j_surf);
enum PeriodicAxis { x, y, z };
RotationalPeriodicBC(int i_surf, int j_surf, PeriodicAxis axis);
double compute_periodic_rotation(
double rise_1, double run_1, double rise_2, double run_2) const;
void handle_particle(Particle& p, const Surface& surf) const override;
protected:
//! Angle about the axis by which particle coordinates will be rotated
double angle_;
//! Do we need to flip surfaces senses when applying the transformation?
bool flip_sense_;
//! Ensure that choice of axes is right handed. axis_1_idx_ corresponds to the
//! independent axis and axis_2_idx_ corresponds to the dependent axis in the
//! 2D plane perpendicular to the planes' axis of rotation
int zero_axis_idx_;
int axis_1_idx_;
int axis_2_idx_;
};
} // namespace openmc

View file

@ -13,12 +13,19 @@ namespace openmc {
//==============================================================================
struct BoundingBox {
double xmin = -INFTY;
double xmax = INFTY;
double ymin = -INFTY;
double ymax = INFTY;
double zmin = -INFTY;
double zmax = INFTY;
Position min = {-INFTY, -INFTY, -INFTY};
Position max = {INFTY, INFTY, INFTY};
// Constructors
BoundingBox() = default;
BoundingBox(Position min_, Position max_) : min {min_}, max {max_} {}
// Static factory methods
static BoundingBox infinite() { return {}; }
static BoundingBox inverted()
{
return {{INFTY, INFTY, INFTY}, {-INFTY, -INFTY, -INFTY}};
}
inline BoundingBox operator&(const BoundingBox& other)
{
@ -35,29 +42,26 @@ struct BoundingBox {
// intersect operator
inline BoundingBox& operator&=(const BoundingBox& other)
{
xmin = std::max(xmin, other.xmin);
xmax = std::min(xmax, other.xmax);
ymin = std::max(ymin, other.ymin);
ymax = std::min(ymax, other.ymax);
zmin = std::max(zmin, other.zmin);
zmax = std::min(zmax, other.zmax);
min.x = std::max(min.x, other.min.x);
min.y = std::max(min.y, other.min.y);
min.z = std::max(min.z, other.min.z);
max.x = std::min(max.x, other.max.x);
max.y = std::min(max.y, other.max.y);
max.z = std::min(max.z, other.max.z);
return *this;
}
// union operator
inline BoundingBox& operator|=(const BoundingBox& other)
{
xmin = std::min(xmin, other.xmin);
xmax = std::max(xmax, other.xmax);
ymin = std::min(ymin, other.ymin);
ymax = std::max(ymax, other.ymax);
zmin = std::min(zmin, other.zmin);
zmax = std::max(zmax, other.zmax);
min.x = std::min(min.x, other.min.x);
min.y = std::min(min.y, other.min.y);
min.z = std::min(min.z, other.min.z);
max.x = std::max(max.x, other.max.x);
max.y = std::max(max.y, other.max.y);
max.z = std::max(max.z, other.max.z);
return *this;
}
inline Position min() const { return {xmin, ymin, zmin}; }
inline Position max() const { return {xmax, ymax, zmax}; }
};
} // namespace openmc

View file

@ -3,7 +3,7 @@
#include "openmc/particle.h"
#include "xtensor/xtensor.hpp"
#include "openmc/tensor.h"
namespace openmc {
@ -14,9 +14,9 @@ namespace openmc {
class BremsstrahlungData {
public:
// Data
xt::xtensor<double, 2> pdf; //!< Bremsstrahlung energy PDF
xt::xtensor<double, 2> cdf; //!< Bremsstrahlung energy CDF
xt::xtensor<double, 1> yield; //!< Photon yield
tensor::Tensor<double> pdf; //!< Bremsstrahlung energy PDF
tensor::Tensor<double> cdf; //!< Bremsstrahlung energy CDF
tensor::Tensor<double> yield; //!< Photon yield
};
class Bremsstrahlung {
@ -32,9 +32,9 @@ public:
namespace data {
extern xt::xtensor<double, 1>
extern tensor::Tensor<double>
ttb_e_grid; //! energy T of incident electron in [eV]
extern xt::xtensor<double, 1>
extern tensor::Tensor<double>
ttb_k_grid; //! reduced energy W/T of emitted photon
} // namespace data

View file

@ -9,14 +9,41 @@
extern "C" {
#endif
//! Run a stochastic volume calculation
//
//! \return Status (negative if an error occurred)
int openmc_calculate_volumes();
int openmc_cell_filter_get_bins(
int32_t index, const int32_t** cells, int32_t* n);
//! Get the fill for a cell
//
//! \param index Index in the cells array
//! \param type Type of the fill
//! \param indices Array of material indices for cell
//! \param n Length of indices array
//! \return Status (negative if an error occurred)
int openmc_cell_get_fill(
int32_t index, int* type, int32_t** indices, int32_t* n);
//! Get the ID of a cell
//
//! \param index Index in the cells array
//! \param id ID of the cell
//! \return Status (negative if an error occurred)
int openmc_cell_get_id(int32_t index, int32_t* id);
//! Get the temperature of a cell
//
//! \param index Index in the cells array
//! \param instance Which instance of the cell. If a null pointer is
//! passed, the temperature of the first instance is returned.
//! \param T temperature of the cell
//!\return Status (negative if an error occurred)
int openmc_cell_get_temperature(
int32_t index, const int32_t* instance, double* T);
int openmc_cell_get_density(
int32_t index, const int32_t* instance, double* rho);
int openmc_cell_get_translation(int32_t index, double xyz[]);
@ -116,15 +143,63 @@ int openmc_mesh_set_id(int32_t index, int32_t id);
int openmc_mesh_get_n_elements(int32_t index, size_t* n);
int openmc_mesh_get_volumes(int32_t index, double* volumes);
int openmc_mesh_material_volumes(int32_t index, int nx, int ny, int nz,
int max_mats, int32_t* materials, double* volumes);
int max_mats, int32_t* materials, double* volumes, double* bboxes);
int openmc_meshsurface_filter_get_mesh(int32_t index, int32_t* index_mesh);
int openmc_meshsurface_filter_set_mesh(int32_t index, int32_t index_mesh);
int openmc_new_filter(const char* type, int32_t* index);
int openmc_next_batch(int* status);
int openmc_nuclide_name(int index, const char** name);
int openmc_plot_geometry();
// Deprecated; use openmc_slice_data.
int openmc_id_map(const void* slice, int32_t* data_out);
// Deprecated; use openmc_slice_data.
int openmc_property_map(const void* slice, double* data_out);
int openmc_slice_data(const double origin[3], const double u_span[3],
const double v_span[3], const size_t pixels[2], bool show_overlaps, int level,
int32_t filter_index, int32_t* geom_data, double* property_data);
int openmc_get_plot_index(int32_t id, int32_t* index);
int openmc_plot_get_id(int32_t index, int32_t* id);
int openmc_plot_set_id(int32_t index, int32_t id);
int openmc_solidraytrace_plot_create(int32_t* index);
int openmc_solidraytrace_plot_get_pixels(
int32_t index, int32_t* width, int32_t* height);
int openmc_solidraytrace_plot_set_pixels(
int32_t index, int32_t width, int32_t height);
int openmc_solidraytrace_plot_get_color_by(int32_t index, int32_t* color_by);
int openmc_solidraytrace_plot_set_color_by(int32_t index, int32_t color_by);
int openmc_solidraytrace_plot_set_default_colors(int32_t index);
int openmc_solidraytrace_plot_set_all_opaque(int32_t index);
int openmc_solidraytrace_plot_set_opaque(
int32_t index, int32_t id, bool visible);
int openmc_solidraytrace_plot_set_color(
int32_t index, int32_t id, uint8_t r, uint8_t g, uint8_t b);
int openmc_solidraytrace_plot_get_camera_position(
int32_t index, double* x, double* y, double* z);
int openmc_solidraytrace_plot_set_camera_position(
int32_t index, double x, double y, double z);
int openmc_solidraytrace_plot_get_look_at(
int32_t index, double* x, double* y, double* z);
int openmc_solidraytrace_plot_set_look_at(
int32_t index, double x, double y, double z);
int openmc_solidraytrace_plot_get_up(
int32_t index, double* x, double* y, double* z);
int openmc_solidraytrace_plot_set_up(
int32_t index, double x, double y, double z);
int openmc_solidraytrace_plot_get_light_position(
int32_t index, double* x, double* y, double* z);
int openmc_solidraytrace_plot_set_light_position(
int32_t index, double x, double y, double z);
int openmc_solidraytrace_plot_get_fov(int32_t index, double* fov);
int openmc_solidraytrace_plot_set_fov(int32_t index, double fov);
int openmc_solidraytrace_plot_update_view(int32_t index);
int openmc_solidraytrace_plot_create_image(
int32_t index, uint8_t* data_out, int32_t width, int32_t height);
int openmc_solidraytrace_plot_get_color(
int32_t index, int32_t id, uint8_t* r, uint8_t* g, uint8_t* b);
int openmc_solidraytrace_plot_get_diffuse_fraction(
int32_t index, double* diffuse_fraction);
int openmc_solidraytrace_plot_set_diffuse_fraction(
int32_t index, double diffuse_fraction);
int openmc_rectilinear_mesh_get_grid(int32_t index, double** grid_x, int* nx,
double** grid_y, int* ny, double** grid_z, int* nz);
int openmc_rectilinear_mesh_set_grid(int32_t index, const double* grid_x,
@ -140,6 +215,7 @@ int openmc_remove_tally(int32_t index);
int openmc_reset();
int openmc_reset_timers();
int openmc_run();
void openmc_run_random_ray();
int openmc_sample_external_source(size_t n, uint64_t* seed, void* sites);
void openmc_set_seed(int64_t new_seed);
void openmc_set_stride(uint64_t new_stride);
@ -201,8 +277,8 @@ int openmc_weight_windows_set_energy_bounds(
int32_t index, double* e_bounds, size_t e_bounds_size);
int openmc_weight_windows_get_energy_bounds(
int32_t index, const double** e_bounds, size_t* e_bounds_size);
int openmc_weight_windows_set_particle(int32_t index, int particle);
int openmc_weight_windows_get_particle(int32_t index, int* particle);
int openmc_weight_windows_set_particle(int32_t index, int32_t particle);
int openmc_weight_windows_get_particle(int32_t index, int32_t* particle);
int openmc_weight_windows_get_bounds(int32_t index, const double** lower_bounds,
const double** upper_bounds, size_t* size);
int openmc_weight_windows_set_bounds(int32_t index, const double* lower_bounds,
@ -218,6 +294,7 @@ int openmc_weight_windows_set_weight_cutoff(int32_t index, double cutoff);
int openmc_weight_windows_get_max_split(int32_t index, int* max_split);
int openmc_weight_windows_set_max_split(int32_t index, int max_split);
size_t openmc_weight_windows_size();
size_t openmc_plots_size();
int openmc_weight_windows_export(const char* filename = nullptr);
int openmc_weight_windows_import(const char* filename = nullptr);
int openmc_zernike_filter_get_order(int32_t index, int* order);
@ -227,10 +304,10 @@ int openmc_zernike_filter_set_order(int32_t index, int order);
int openmc_zernike_filter_set_params(
int32_t index, const double* x, const double* y, const double* r);
int openmc_particle_filter_get_bins(int32_t idx, int bins[]);
int openmc_particle_filter_get_bins(int32_t idx, int32_t bins[]);
//! Sets the mesh and energy grid for CMFD reweight
//! \param[in] meshtyally_id id of CMFD Mesh Tally
//! \param[in] meshtally_id id of CMFD Mesh Tally
//! \param[in] cmfd_indices indices storing spatial and energy dimensions of
//! CMFD problem \param[in] norm CMFD normalization factor
void openmc_initialize_mesh_egrid(

View file

@ -123,11 +123,11 @@ private:
//! BoundingBox if the particle is in a complex cell.
BoundingBox bounding_box_complex(vector<int32_t> postfix) const;
//! Enfource precedence: Parenthases, Complement, Intersection, Union
void add_precedence();
//! Enforce precedence between intersections and unions
void enforce_precedence();
//! Add parenthesis to enforce precedence
int64_t add_parentheses(int64_t start);
void add_parentheses(int64_t start);
//! Remove complement operators from the expression
void remove_complement_ops();
@ -145,6 +145,30 @@ private:
bool simple_; //!< Does the region contain only intersections?
};
//==============================================================================
// XML parsing helpers for <cell> nodes
//==============================================================================
//! Parse material IDs from a <cell> XML node.
//! \param node XML node containing a "material" attribute or child element
//! \param cell_id Cell ID used in error messages
//! \return Vector of material IDs (MATERIAL_VOID for "void")
vector<int32_t> parse_cell_material_xml(pugi::xml_node node, int32_t cell_id);
//! Parse temperatures in [K] from a <cell> XML node.
//! Validates that all values are non-negative and the list is non-empty.
//! \param node XML node containing a "temperature" attribute or child element
//! \param cell_id Cell ID used in error messages
//! \return Vector of temperatures in [K]
vector<double> parse_cell_temperature_xml(pugi::xml_node node, int32_t cell_id);
//! Parse densities in [g/cm³] from a <cell> XML node.
//! Validates that all values are positive and the list is non-empty.
//! \param node XML node containing a "density" attribute or child element
//! \param cell_id Cell ID used in error messages
//! \return Vector of densities in [g/cm³]
vector<double> parse_cell_density_xml(pugi::xml_node node, int32_t cell_id);
//==============================================================================
class Cell {

View file

@ -71,6 +71,15 @@ public:
void sample(
double E_in, double& E_out, double& mu, uint64_t* seed) const override;
//! Sample an outgoing energy and evaluate the angular PDF
//! \param[in] E_in Incoming energy in [eV]
//! \param[in] mu Scattering cosine with respect to current direction
//! \param[out] E_out Outgoing energy in [eV]
//! \param[inout] seed Pseudorandom seed pointer
//! \return Probability density for the scattering cosine
double sample_energy_and_pdf(
double E_in, double mu, double& E_out, uint64_t* seed) const override;
private:
const Distribution* photon_energy_;
};
@ -92,6 +101,8 @@ extern vector<unique_ptr<ChainNuclide>> chain_nuclides;
void read_chain_file_xml();
void free_memory_chain();
} // namespace openmc
#endif // OPENMC_CHAIN_H

View file

@ -9,6 +9,7 @@
#include <limits>
#include "openmc/array.h"
#include "openmc/atomic_mass.h"
#include "openmc/vector.h"
#include "openmc/version.h"
@ -25,16 +26,16 @@ using double_4dvec = vector<vector<vector<vector<double>>>>;
constexpr int HDF5_VERSION[] {3, 0};
// Version numbers for binary files
constexpr array<int, 2> VERSION_STATEPOINT {18, 1};
constexpr array<int, 2> VERSION_PARTICLE_RESTART {2, 0};
constexpr array<int, 2> VERSION_TRACK {3, 0};
constexpr array<int, 2> VERSION_STATEPOINT {18, 2};
constexpr array<int, 2> VERSION_PARTICLE_RESTART {2, 1};
constexpr array<int, 2> VERSION_TRACK {3, 1};
constexpr array<int, 2> VERSION_SUMMARY {6, 1};
constexpr array<int, 2> VERSION_VOLUME {1, 0};
constexpr array<int, 2> VERSION_VOXEL {2, 0};
constexpr array<int, 2> VERSION_MGXS_LIBRARY {1, 0};
constexpr array<int, 2> VERSION_PROPERTIES {1, 1};
constexpr array<int, 2> VERSION_WEIGHT_WINDOWS {1, 0};
constexpr array<int, 2> VERSION_COLLISION_TRACK {1, 0};
constexpr array<int, 2> VERSION_COLLISION_TRACK {1, 2};
// ============================================================================
// ADJUSTABLE PARAMETERS
@ -86,10 +87,10 @@ constexpr double INFTY {std::numeric_limits<double>::max()};
// (CODATA) 2018 recommendation (https://physics.nist.gov/cuu/Constants/).
// Physical constants
constexpr double MASS_NEUTRON {1.00866491595}; // mass of a neutron in amu
constexpr double AMU_EV {
9.3149410242e8}; // atomic mass unit energy equivalent in eV/c^2
constexpr double MASS_NEUTRON_EV {
939.56542052e6}; // mass of a neutron in eV/c^2
constexpr double MASS_PROTON {1.007276466621}; // mass of a proton in amu
939.56542052e6}; // neutron mass energy equivalent in eV/c^2
constexpr double MASS_ELECTRON_EV {
0.51099895000e6}; // electron mass energy equivalent in eV/c^2
constexpr double FINE_STRUCTURE {
@ -226,6 +227,7 @@ enum ReactionType {
N_XA = 207,
HEATING = 301,
DAMAGE_ENERGY = 444,
PHOTON_TOTAL = 501,
COHERENT = 502,
INCOHERENT = 504,
PAIR_PROD_ELEC = 515,
@ -301,7 +303,7 @@ enum class TallyEstimator { ANALOG, TRACKLENGTH, COLLISION };
enum class TallyEvent { SURFACE, LATTICE, KILL, SCATTER, ABSORB };
// Tally score type -- if you change these, make sure you also update the
// _SCORES dictionary in openmc/capi/tally.py
// _SCORES dictionary in openmc/lib/tally.py
//
// These are kept as a normal enum and made negative, since variables which
// store one of these enum values usually also may be responsible for storing
@ -365,7 +367,8 @@ enum class SolverType { MONTE_CARLO, RANDOM_RAY };
enum class RandomRayVolumeEstimator { NAIVE, SIMULATION_AVERAGED, HYBRID };
enum class RandomRaySourceShape { FLAT, LINEAR, LINEAR_XY };
enum class RandomRaySampleMethod { PRNG, HALTON };
enum class RandomRaySampleMethod { PRNG, HALTON, S2 };
enum class RandomRaySolve { FORWARD, FORWARD_FOR_ADJOINT, ADJOINT };
//==============================================================================
// Geometry Constants

View file

@ -94,6 +94,10 @@ private:
class DAGUniverse : public Universe {
public:
using MaterialOverrides = std::unordered_map<int32_t, vector<int32_t>>;
using TemperatureOverrides = std::unordered_map<int32_t, vector<double>>;
using DensityOverrides = std::unordered_map<int32_t, vector<double>>;
explicit DAGUniverse(pugi::xml_node node);
//! Create a new DAGMC universe
@ -112,6 +116,9 @@ public:
//! Initialize the DAGMC accel. data structures, indices, material
//! assignments, etc.
void initialize();
void initialize(const MaterialOverrides& material_overrides,
const TemperatureOverrides& temperature_overrides,
const DensityOverrides& density_overrides = {});
//! Reads UWUW materials and returns an ID map
void read_uwuw_materials();
@ -146,7 +153,8 @@ public:
//! Assign a material overriding normal assignement to a cell
//! \param[in] c The OpenMC cell to which the material is assigned
void override_assign_material(std::unique_ptr<DAGCell>& c) const;
void override_assign_material(std::unique_ptr<DAGCell>& c,
const MaterialOverrides& material_overrides) const;
//! Return the index into the model cells vector for a given DAGMC volume
//! handle in the universe
@ -187,7 +195,9 @@ private:
void set_id(); //!< Deduce the universe id from model::universes
void init_dagmc(); //!< Create and initialise DAGMC pointer
void init_metadata(); //!< Create and initialise dagmcMetaData pointer
void init_geometry(); //!< Create cells and surfaces from DAGMC entities
void init_geometry(const MaterialOverrides& material_overrides,
const TemperatureOverrides& temperature_overrides,
const DensityOverrides& density_overrides);
std::string
filename_; //!< Name of the DAGMC file used to create this universe
@ -201,11 +211,6 @@ private:
//!< generate new material IDs for the universe
bool has_graveyard_; //!< Indicates if the DAGMC geometry has a "graveyard"
//!< volume
std::unordered_map<int32_t, vector<int32_t>>
material_overrides_; //!< Map of material overrides
//!< keys correspond to the DAGMCCell id
//!< values are a list of material ids used
//!< for the override
};
//==============================================================================

View file

@ -15,6 +15,17 @@
namespace openmc {
//==============================================================================
// Helper function for computing importance weights from biased sampling
//==============================================================================
//! Compute importance weights for biased sampling
//! \param p Unnormalized original probability vector
//! \param b Unnormalized bias probability vector
//! \return Vector of importance weights (p_norm[i] / b_norm[i])
vector<double> compute_importance_weights(
const vector<double>& p, const vector<double>& b);
//==============================================================================
//! Abstract class representing a univariate probability distribution
//==============================================================================
@ -22,11 +33,41 @@ namespace openmc {
class Distribution {
public:
virtual ~Distribution() = default;
virtual double sample(uint64_t* seed) const = 0;
//! Sample a value from the distribution, handling biasing automatically
//! \param seed Pseudorandom number seed pointer
//! \return (sampled value, importance weight)
virtual std::pair<double, double> sample(uint64_t* seed) const;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
virtual double evaluate(double x) const;
//! Return integral of distribution
//! \return Integral of distribution
virtual double integral() const { return 1.0; };
//! Set bias distribution
virtual void set_bias(std::unique_ptr<Distribution> bias)
{
bias_ = std::move(bias);
}
const Distribution* bias() const { return bias_.get(); }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
virtual double sample_unbiased(uint64_t* seed) const = 0;
//! Read bias distribution from XML
//! \param node XML node that may contain a bias child element
void read_bias_from_xml(pugi::xml_node node);
// Biasing distribution
unique_ptr<Distribution> bias_;
};
using UPtrDist = unique_ptr<Distribution>;
@ -50,7 +91,7 @@ public:
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
//! \return Sampled index
size_t sample(uint64_t* seed) const;
// Properties
@ -67,7 +108,7 @@ private:
//! Normalize distribution so that probabilities sum to unity
void normalize();
//! Initialize alias tables for distribution
//! Initialize alias table for sampling
void init_alias();
};
@ -82,20 +123,30 @@ public:
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! \return (sampled value, sample weight)
std::pair<double, double> sample(uint64_t* seed) const override;
double integral() const override { return di_.integral(); };
//! Override set_bias as no-op (bias handled in constructor)
void set_bias(std::unique_ptr<Distribution> bias) override {}
// Properties
const vector<double>& x() const { return x_; }
const vector<double>& prob() const { return di_.prob(); }
const vector<size_t>& alias() const { return di_.alias(); }
const vector<double>& weight() const { return weight_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
vector<double> x_; //!< Possible outcomes
DiscreteIndex di_; //!< discrete probability distribution of
//!< outcome indices
vector<double> x_; //!< Possible outcomes
vector<double> weight_; //!< Importance weights (empty if unbiased)
DiscreteIndex di_; //!< Discrete probability distribution of outcome indices
};
//==============================================================================
@ -107,14 +158,20 @@ public:
explicit Uniform(pugi::xml_node node);
Uniform(double a, double b) : a_ {a}, b_ {b} {};
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
double a() const { return a_; }
double b() const { return b_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
double a_; //!< Lower bound of distribution
double b_; //!< Upper bound of distribution
@ -131,15 +188,21 @@ public:
: offset_ {std::pow(a, n + 1)}, span_ {std::pow(b, n + 1) - offset_},
ninv_ {1 / (n + 1)} {};
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
double a() const { return std::pow(offset_, ninv_); }
double b() const { return std::pow(offset_ + span_, ninv_); }
double n() const { return 1 / ninv_ - 1; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
//! Store processed values in object to allow for faster sampling
double offset_; //!< a^(n+1)
@ -156,13 +219,19 @@ public:
explicit Maxwell(pugi::xml_node node);
Maxwell(double theta) : theta_ {theta} {};
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
double theta() const { return theta_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
double theta_; //!< Factor in exponential [eV]
};
@ -176,41 +245,66 @@ public:
explicit Watt(pugi::xml_node node);
Watt(double a, double b) : a_ {a}, b_ {b} {};
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
double a() const { return a_; }
double b() const { return b_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
double a_; //!< Factor in exponential [eV]
double b_; //!< Factor in square root [1/eV]
};
//==============================================================================
//! Normal distributions with form 1/2*std_dev*sqrt(pi) exp
//! (-(e-E0)/2*std_dev)^2
//! Normal distribution with optional truncation bounds.
//!
//! The standard normal PDF is 1/(sqrt(2*pi)*sigma) *
//! exp(-(x-mu)^2/(2*sigma^2)). When truncated to [lower, upper], the PDF is
//! renormalized so that it integrates to 1 over the truncation interval.
//==============================================================================
class Normal : public Distribution {
public:
explicit Normal(pugi::xml_node node);
Normal(double mean_value, double std_dev)
: mean_value_ {mean_value}, std_dev_ {std_dev} {};
Normal(double mean_value, double std_dev, double lower = -INFTY,
double upper = INFTY);
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x), accounting for truncation normalization
double evaluate(double x) const override;
double mean_value() const { return mean_value_; }
double std_dev() const { return std_dev_; }
double lower() const { return lower_; }
double upper() const { return upper_; }
bool is_truncated() const { return is_truncated_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
double mean_value_; //!< middle of distribution [eV]
double std_dev_; //!< standard deviation [eV]
double mean_value_; //!< Mean of distribution
double std_dev_; //!< Standard deviation
double lower_; //!< Lower truncation bound (default: -INFTY)
double upper_; //!< Upper truncation bound (default: +INFTY)
bool is_truncated_; //!< True if bounds are finite
double norm_factor_; //!< Normalization factor for truncated distribution
//! Compute normalization factor for truncated distribution
void compute_normalization();
};
//==============================================================================
@ -223,10 +317,10 @@ public:
Tabular(const double* x, const double* p, int n, Interpolation interp,
const double* c = nullptr);
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
// properties
vector<double>& x() { return x_; }
@ -235,6 +329,12 @@ public:
Interpolation interp() const { return interp_; }
double integral() const override { return integral_; };
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
vector<double> x_; //!< tabulated independent variable
vector<double> p_; //!< tabulated probability density
@ -259,13 +359,19 @@ public:
explicit Equiprobable(pugi::xml_node node);
Equiprobable(const double* x, int n) : x_ {x, x + n} {};
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! Evaluate probability density, f(x), at a point
//! \param x Point to evaluate f(x)
//! \return f(x)
double evaluate(double x) const override;
const vector<double>& x() const { return x_; }
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
vector<double> x_; //! Possible outcomes
};
@ -280,18 +386,90 @@ public:
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample(uint64_t* seed) const override;
//! \return (sampled value, sample weight)
std::pair<double, double> sample(uint64_t* seed) const override;
double integral() const override { return integral_; }
private:
// Storrage for probability + distribution
using DistPair = std::pair<double, UPtrDist>;
//! Override set_bias as no-op (bias handled in constructor)
void set_bias(std::unique_ptr<Distribution> bias) override {}
vector<DistPair>
distribution_; //!< sub-distributions + cummulative probabilities
double integral_; //!< integral of distribution
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
vector<UPtrDist> distribution_; //!< Sub-distributions
vector<double> weight_; //!< Importance weights for component selection
DiscreteIndex di_; //!< Discrete probability distribution of indices
double integral_; //!< Integral of distribution
};
//==============================================================================
// DecaySpectrum — non-owning mixture of decay photon distributions
//==============================================================================
//! Energy distribution formed by mixing multiple decay photon spectra.
//!
//! Unlike the general Mixture distribution, this class holds non-owning
//! pointers to the component distributions (which live in
//! data::chain_nuclides). Each component is weighted by the activity
//! (atoms * decay_constant) of the corresponding nuclide.
class DecaySpectrum : public Distribution {
public:
//============================================================================
// Types, aliases
struct Sample {
double energy;
double weight;
int parent_nuclide;
};
//============================================================================
// Constructors
//! Construct from an XML node containing nuclide names and atom densities.
//!
//! Reads child ``<nuclide>`` elements with ``name`` and ``density``
//! attributes, resolves them against the loaded depletion chain, and
//! constructs the mixed distribution.
explicit DecaySpectrum(pugi::xml_node node);
//============================================================================
// Methods
//! Sample a value from the distribution and return the parent nuclide index
//! \param seed Pseudorandom number seed pointer
//! \return (Sampled energy, sample weight, chain nuclide index)
Sample sample_with_parent(uint64_t* seed) const;
//! Sample a value from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return (sampled value, sample weight)
std::pair<double, double> sample(uint64_t* seed) const override;
double integral() const override;
protected:
//! Sample a value (unbiased) from the distribution
//! \param seed Pseudorandom number seed pointer
//! \return Sampled value
double sample_unbiased(uint64_t* seed) const override;
private:
//! Initialize decay spectrum sampling data
//! \param nuclide_indices Indices of decay photon emitters in
//! data::chain_nuclides
//! \param atoms Number of atoms for each component.
void init(vector<int> nuclide_indices, const vector<double>& atoms);
vector<int> nuclide_indices_; //!< Indices of emitting nuclides in the chain
DiscreteIndex di_; //!< Discrete index for component selection
double integral_; //!< Total photon emission rate
};
} // namespace openmc

View file

@ -26,6 +26,12 @@ public:
//! \return Cosine of the angle in the range [-1,1]
double sample(double E, uint64_t* seed) const;
//! Evaluate the angular PDF at a given energy and cosine
//! \param[in] E Particle energy in [eV]
//! \param[in] mu Cosine of the scattering angle
//! \return Probability density for the scattering cosine
double evaluate(double E, double mu) const;
//! Determine whether angle distribution is empty
//! \return Whether distribution is empty
bool empty() const { return energy_.empty(); }

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