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ecb0a3361f
Co-authored-by: Gavin Ridley <gavin.keith.ridley@gmail.com> Co-authored-by: Paul Romano <paul.k.romano@gmail.com>
101 lines
3.3 KiB
Python
101 lines
3.3 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import openmc
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###############################################################################
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# Create materials for the problem
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uo2 = openmc.Material(name="UO2 fuel at 2.4% wt enrichment")
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uo2.set_density("g/cm3", 10.29769)
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uo2.add_element("U", 1.0, enrichment=2.4)
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uo2.add_element("O", 2.0)
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helium = openmc.Material(name="Helium for gap")
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helium.set_density("g/cm3", 0.001598)
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helium.add_element("He", 2.4044e-4)
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zircaloy = openmc.Material(name="Zircaloy 4")
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zircaloy.set_density("g/cm3", 6.55)
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zircaloy.add_element("Sn", 0.014, "wo")
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zircaloy.add_element("Fe", 0.00165, "wo")
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zircaloy.add_element("Cr", 0.001, "wo")
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zircaloy.add_element("Zr", 0.98335, "wo")
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borated_water = openmc.Material(name="Borated water")
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borated_water.set_density("g/cm3", 0.740582)
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borated_water.add_element("B", 2.0e-4) # 3x the original pincell
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borated_water.add_element("H", 5.0e-2)
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borated_water.add_element("O", 2.4e-2)
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borated_water.add_s_alpha_beta("c_H_in_H2O")
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###############################################################################
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# Define problem geometry
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# Create cylindrical surfaces
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fuel_or = openmc.ZCylinder(r=0.39218, name="Fuel OR")
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clad_ir = openmc.ZCylinder(r=0.40005, name="Clad IR")
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clad_or = openmc.ZCylinder(r=0.45720, name="Clad OR")
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# Create a region represented as the inside of a rectangular prism
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pitch = 1.25984
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box = openmc.model.RectangularPrism(pitch, pitch, boundary_type="reflective")
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# Create cells, mapping materials to regions
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fuel = openmc.Cell(fill=uo2, region=-fuel_or)
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gap = openmc.Cell(fill=helium, region=+fuel_or & -clad_ir)
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clad = openmc.Cell(fill=zircaloy, region=+clad_ir & -clad_or)
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water = openmc.Cell(fill=borated_water, region=+clad_or & -box)
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# Create a model and assign geometry
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model = openmc.Model()
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model.geometry = openmc.Geometry([fuel, gap, clad, water])
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###############################################################################
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# Define problem settings
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# Set the mode
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model.settings.run_mode = "fixed source"
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# Indicate how many batches and particles to run
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model.settings.batches = 10
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model.settings.particles = 10000
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# Set time cutoff (we only care about t < 100 seconds, see tally below)
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model.settings.cutoff = {"time_neutron": 100}
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# Create the neutron pulse source (by default, isotropic direction, t=0)
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space = openmc.stats.Point() # At the origin (0, 0, 0)
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energy = openmc.stats.delta_function(14.1e6) # At 14.1 MeV
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model.settings.source = openmc.IndependentSource(space=space, energy=energy)
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###############################################################################
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# Define tallies
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# Create time filter
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t_grid = np.insert(np.logspace(-6, 2, 100), 0, 0.0)
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time_filter = openmc.TimeFilter(t_grid)
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# Tally for total neutron density in time
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density_tally = openmc.Tally(name="Density")
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density_tally.filters = [time_filter]
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density_tally.scores = ["inverse-velocity"]
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# Add tallies to model
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model.tallies = openmc.Tallies([density_tally])
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# Run the model
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model.run(apply_tally_results=True)
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# Bin-averaged result
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density_mean = density_tally.mean.ravel() / np.diff(t_grid)
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# Plot particle density versus time
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fig, ax = plt.subplots()
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ax.stairs(density_mean, t_grid)
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ax.set_xscale("log")
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ax.set_yscale("log")
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ax.set_xlabel("Time [s]")
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ax.set_ylabel("Total density")
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ax.grid()
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plt.show()
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