added comments

tasks/task_14_activation_transmutation_depletion/3_full_pulse_schedule.py

@@ -1,8 +1,10 @@
 # This example performs a depletion simulation using the IndependentOperator
 # instead of the CoupledOperator used in the first examples.
 
-# This is an approximation so is less accurate but it is faster and might be
-# still sufficiently accurate for your use case.
+# This is an approximation so is less accurate but it is much faster.
+# This approach performs just a single transport simulation and obtains reactions rates once.
+# If the materials don't change significantly during the irradiation this is a reasonable approximation.
+# Fission fule pins would perhaps require the CoupledOperator while the majority of fusion simulations are suitable for the IndependentOperator
 
 # More details on both Operators in the docs
 # https://docs.openmc.org/en/stable/usersguide/depletion.html#transport-independent-depletion
@@ -11,43 +13,61 @@
 import openmc.deplete
 import math
 import matplotlib.pyplot as plt
+
+# chain and cross section paths have been set on the docker image but you may want to change them
 #openmc.config['chain_file']=/home/j/openmc_data/chain-endf-b8.0.xml
 #openmc.config['cross_sections']=/home/j/nndc-b8.0-hdf5/endfb-viii.0-hdf5/cross_sections.xml
+
+# Creates a simple material
 my_material = openmc.Material() 
 my_material.add_element('Ag', 1, percent_type='ao')
 my_material.set_density('g/cm3', 10.49)
+
+# As we are doing a depletion simulation we must set the material volume and the .depletion to True
 sphere_radius = 100
 volume_of_sphere = (4/3) * math.pi * math.pow(sphere_radius, 3)
 my_material.volume = volume_of_sphere  # a volume is needed so openmc can find the number of atoms in the cell/material
 my_material.depletable = True  # depletable = True is needed to tell openmc to update the material with each time step
+
 materials = openmc.Materials([my_material])
+
+# makes a simple sphere surface and cell
 sph1 = openmc.Sphere(r=sphere_radius, boundary_type='vacuum')
 shield_cell = openmc.Cell(region=-sph1)
 shield_cell.fill = my_material
 geometry = openmc.Geometry([shield_cell])
+
+# creates a simple point source
 source = openmc.IndependentSource()
 source.space = openmc.stats.Point((0, 0, 0))
 source.angle = openmc.stats.Isotropic()
 source.energy = openmc.stats.Discrete([14e6], [1])
 source.particles = 'neutron'
+
 settings = openmc.Settings()
 settings.batches = 10
 settings.inactive = 0
 settings.particles = 1000
 settings.source = source
 settings.run_mode = 'fixed source'
+
 model = openmc.model.Model(geometry, materials, settings)
-# this does perform transport but just to get the flux, the flux could also be input in the energy group format (ccfe 709 used here)
+
+# this does perform transport but just to get the flux and micro xs
 flux_in_each_group, micro_xs = openmc.deplete.get_microxs_and_flux(
     model=model,
     domains=[shield_cell],
     energies='CCFE-709',
 )
+
+# Plotting the neutron spectra
 plt.title('neutron flux spectra')
 plt.plot(openmc.mgxs.GROUP_STRUCTURES['CCFE-709'][:-1], flux_in_each_group[0])
 plt.xscale('log')
 plt.yscale('log')
 plt.show()
+
+# constructing the operator, note we pass in the flux and micro xs
 operator = openmc.deplete.IndependentOperator(
     materials=materials,
     fluxes=flux_in_each_group,
@@ -56,6 +76,7 @@
     reduce_chain_level=5,
     normalization_mode="source-rate"
 )
+
 # We define timesteps together with the source rate to make it clearer
 timesteps_and_source_rates = [
     (24, 1e20),
@@ -84,17 +105,26 @@
 timesteps = [item[0] for item in timesteps_and_source_rates]
 source_rates = [item[1] for item in timesteps_and_source_rates]
 
+# construct the integrator
 integrator = openmc.deplete.PredictorIntegrator(
     operator=operator,
     timesteps=timesteps,
     source_rates=source_rates,
     timestep_units='s'
 )
+
+# this runs the depltion calculations for the timesteps
 integrator.integrate()
+
+# Loads up the results
 results = openmc.deplete.ResultsList.from_hdf5("depletion_results.h5")
 times, number_of_Ag110_atoms = results.get_atoms(my_material, 'Ag110')
+
+# prints the atoms in a table
 for time, num in zip(times, number_of_Ag110_atoms):
     print(f" Time {time}s. Number of Ag110 atoms {num}")
+
+# plots the number of atoms as a function of time
 plt.cla()
 plt.clf()
 plt.plot(times, number_of_Ag110_atoms)