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202 lines
8.4 KiB
Python
202 lines
8.4 KiB
Python
import numpy as np
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import openmc
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import openmc.mgxs
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###############################################################################
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# Create multigroup data
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# Instantiate the energy group data
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group_edges = [1e-5, 0.0635, 10.0, 1.0e2, 1.0e3, 0.5e6, 1.0e6, 20.0e6]
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groups = openmc.mgxs.EnergyGroups(group_edges)
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# Instantiate the 7-group (C5G7) cross section data
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uo2_xsdata = openmc.XSdata('UO2', groups)
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uo2_xsdata.order = 0
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uo2_xsdata.set_total(
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[0.1779492, 0.3298048, 0.4803882, 0.5543674, 0.3118013, 0.3951678,
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0.5644058])
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uo2_xsdata.set_absorption([8.0248e-03, 3.7174e-03, 2.6769e-02, 9.6236e-02,
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3.0020e-02, 1.1126e-01, 2.8278e-01])
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scatter_matrix = np.array(
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[[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
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[0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
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[0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000],
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[0.0000000, 0.0000000, 0.0000000, 0.4525650, 0.0055664, 0.0000000, 0.0000000],
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[0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]])
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scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
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uo2_xsdata.set_scatter_matrix(scatter_matrix)
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uo2_xsdata.set_fission([7.21206e-03, 8.19301e-04, 6.45320e-03,
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1.85648e-02, 1.78084e-02, 8.30348e-02,
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2.16004e-01])
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uo2_xsdata.set_nu_fission([2.005998e-02, 2.027303e-03, 1.570599e-02,
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4.518301e-02, 4.334208e-02, 2.020901e-01,
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5.257105e-01])
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uo2_xsdata.set_chi([5.8791e-01, 4.1176e-01, 3.3906e-04, 1.1761e-07, 0.0000e+00,
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0.0000e+00, 0.0000e+00])
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h2o_xsdata = openmc.XSdata('LWTR', groups)
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h2o_xsdata.order = 0
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h2o_xsdata.set_total([0.15920605, 0.412969593, 0.59030986, 0.58435,
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0.718, 1.2544497, 2.650379])
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h2o_xsdata.set_absorption([6.0105e-04, 1.5793e-05, 3.3716e-04,
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1.9406e-03, 5.7416e-03, 1.5001e-02,
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3.7239e-02])
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scatter_matrix = np.array(
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[[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000],
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[0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010],
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[0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034],
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[0.0000000, 0.0000000, 0.0000000, 0.0910284, 0.4155100, 0.0637320, 0.0121390],
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[0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200],
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[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]])
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scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
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h2o_xsdata.set_scatter_matrix(scatter_matrix)
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mg_cross_sections_file = openmc.MGXSLibrary(groups)
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mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata])
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mg_cross_sections_file.export_to_hdf5()
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###############################################################################
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# Create materials for the problem
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# Instantiate some Materials and register the appropriate macroscopic data
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uo2 = openmc.Material(name='UO2 fuel')
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uo2.set_density('macro', 1.0)
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uo2.add_macroscopic('UO2')
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water = openmc.Material(name='Water')
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water.set_density('macro', 1.0)
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water.add_macroscopic('LWTR')
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# Instantiate a Materials collection and export to XML
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materials_file = openmc.Materials([uo2, water])
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materials_file.cross_sections = "mgxs.h5"
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materials_file.export_to_xml()
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###############################################################################
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# Define problem geometry
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# The geometry we will define a simplified pincell with fuel radius 0.54 cm
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# surrounded by moderator (same as in the multigroup example).
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# In random ray, we typically want several radial regions and azimuthal
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# sectors in both the fuel and moderator areas of the pincell. This is
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# due to the flat source approximation requiring that source regions are
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# small compared to the typical mean free path of a neutron. Below we
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# sudivide the basic pincell into 8 aziumthal sectors (pizza slices) and
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# 5 concentric rings in both the fuel and moderator.
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# TODO: When available in OpenMC, use cylindrical lattice instead to
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# simplify definition and improve runtime performance.
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pincell_base = openmc.Universe()
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# These are the subdivided radii (creating 5 concentric regions in the
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# fuel and moderator)
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ring_radii = [0.241, 0.341, 0.418, 0.482, 0.54, 0.572, 0.612, 0.694, 0.786]
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fills = [uo2, uo2, uo2, uo2, uo2, water, water, water, water, water]
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# We then create cells representing the bounded rings, with special
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# treatment for both the innermost and outermost cells
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cells = []
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for r in range(10):
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cell = []
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if r == 0:
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outer_bound = openmc.ZCylinder(r=ring_radii[r])
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cell = openmc.Cell(fill=fills[r], region=-outer_bound)
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elif r == 9:
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inner_bound = openmc.ZCylinder(r=ring_radii[r-1])
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cell = openmc.Cell(fill=fills[r], region=+inner_bound)
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else:
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inner_bound = openmc.ZCylinder(r=ring_radii[r-1])
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outer_bound = openmc.ZCylinder(r=ring_radii[r])
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cell = openmc.Cell(fill=fills[r], region=+inner_bound & -outer_bound)
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pincell_base.add_cell(cell)
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# We then generate 8 planes to bound 8 azimuthal sectors
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azimuthal_planes = []
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for i in range(8):
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angle = 2 * i * openmc.pi / 8
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normal_vector = (-openmc.sin(angle), openmc.cos(angle), 0)
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azimuthal_planes.append(openmc.Plane(a=normal_vector[0], b=normal_vector[1], c=normal_vector[2], d=0))
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# Create a cell for each azimuthal sector using the pincell base class
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azimuthal_cells = []
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for i in range(8):
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azimuthal_cell = openmc.Cell(name=f'azimuthal_cell_{i}')
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azimuthal_cell.fill = pincell_base
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azimuthal_cell.region = +azimuthal_planes[i] & -azimuthal_planes[(i+1) % 8]
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azimuthal_cells.append(azimuthal_cell)
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# Create the (subdivided) geometry with the azimuthal universes
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pincell = openmc.Universe(cells=azimuthal_cells)
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# Create a region represented as the inside of a rectangular prism
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pitch = 1.26
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box = openmc.model.RectangularPrism(pitch, pitch, boundary_type='reflective')
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pincell_bounded = openmc.Cell(fill=pincell, region=-box, name='pincell')
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# Create a geometry (specifying merge surfaces option to remove
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# all the redundant cylinder/plane surfaces) and export to XML
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geometry = openmc.Geometry([pincell_bounded], merge_surfaces=True)
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geometry.export_to_xml()
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###############################################################################
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# Define problem settings
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# Instantiate a Settings object, set all runtime parameters, and export to XML
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settings = openmc.Settings()
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settings.energy_mode = "multi-group"
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settings.batches = 600
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settings.inactive = 300
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settings.particles = 50
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# Create an initial uniform spatial source distribution for sampling rays.
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# Note that this must be uniform in space and angle.
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lower_left = (-pitch/2, -pitch/2, -1)
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upper_right = (pitch/2, pitch/2, 1)
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uniform_dist = openmc.stats.Box(lower_left, upper_right)
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settings.random_ray['ray_source'] = openmc.IndependentSource(space=uniform_dist)
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settings.random_ray['distance_inactive'] = 40.0
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settings.random_ray['distance_active'] = 400.0
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settings.export_to_xml()
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###############################################################################
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# Define tallies
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# Create a mesh that will be used for tallying
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mesh = openmc.RegularMesh()
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mesh.dimension = (2, 2)
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mesh.lower_left = (-pitch/2, -pitch/2)
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mesh.upper_right = (pitch/2, pitch/2)
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# Create a mesh filter that can be used in a tally
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mesh_filter = openmc.MeshFilter(mesh)
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# Let's also create a filter to measure each group
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# indepdendently
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energy_filter = openmc.EnergyFilter(group_edges)
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# Now use the mesh filter in a tally and indicate what scores are desired
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tally = openmc.Tally(name="Mesh and Energy tally")
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tally.filters = [mesh_filter, energy_filter]
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tally.scores = ['flux', 'fission', 'nu-fission']
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# Instantiate a Tallies collection and export to XML
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tallies = openmc.Tallies([tally])
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tallies.export_to_xml()
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###############################################################################
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# Exporting to OpenMC plots.xml file
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###############################################################################
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plot = openmc.VoxelPlot()
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plot.origin = [0, 0, 0]
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plot.width = [pitch, pitch, pitch]
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plot.pixels = [1000, 1000, 1]
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# Instantiate a Plots collection and export to XML
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plots = openmc.Plots([plot])
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plots.export_to_xml()
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