In [10]:

from collections import defaultdict
import matplotlib.pyplot as plt
import openmc.deplete
import openmc.data

In [3]:

chain = openmc.deplete.Chain.from_xml('/home/romano/openmc-data/depletion/chain_casl_pwr.xml')

In [4]:

u235 = chain['U235']

In [5]:

u235.yield_data

Out[5]:

<FissionYieldDistribution with 155 products at 3 energies>

The yield data is organized by incident neutron energy

In [6]:

u235.yield_data.energies

Out[6]:

(0.0253, 500000.0, 14000000.0)

You can index the yield data by energy:

In [7]:

thermal_yield = u235.yield_data[0.0253]
thermal_yield

Out[7]:

<FissionYield containing 155 products and yields>

And then by a product:

In [8]:

thermal_yield['I135']

Out[8]:

0.0628187

thermal_yield will act as a dictionary, so you can use methods like items() on it:

In [9]:

list(thermal_yield.items())

Out[9]:

[('Ag109', 0.0),
 ('Ag109_m1', 0.0),
 ('Ag110', 1.00993e-14),
 ('Ag110_m1', 2.27984e-14),
 ('Ag111', 0.000173788),
 ('Ba134', 5.25963e-12),
 ('Ba137', 5.42962e-07),
 ('Ba140', 0.0621448),
 ('Br81', 0.00203666),
 ('Br82', 5.41962e-07),
 ('Cd110', 0.0),
 ('Cd111', 5.200000000000018e-07),
 ('Cd113', 0.00014038),
 ('Ce140', 1.14992e-09),
 ('Ce141', 0.0584699),
 ('Ce142', 0.0584879),
 ('Ce143', 0.0595576),
 ('Ce144', 0.0549956),
 ('Cs133', 7.91944e-09),
 ('Cs134', 3.85473e-08),
 ('Cs135', 2.45483e-06),
 ('Cs136', 2.7688e-05),
 ('Cs137', 0.000599988),
 ('Dy160', 1.92986e-14),
 ('Dy161', 2.50982e-13),
 ('Dy162', 1.58989e-07),
 ('Dy163', 6.10957e-08),
 ('Dy164', 1.87987e-08),
 ('Dy165', 9.39934e-09),
 ('Eu151', 2.48982e-12),
 ('Eu153', 2.32984e-09),
 ('Eu154', 9.69931e-10),
 ('Eu155', 2.62981e-08),
 ('Eu156', 0.00014853),
 ('Eu157', 6.14957e-05),
 ('Gd154', 1.11992e-13),
 ('Gd155', 4.07971e-12),
 ('Gd156', 1.4299e-10),
 ('Gd157', 1.4799e-09),
 ('Gd158', 3.28577e-05),
 ('Gd159', 1.00893e-05),
 ('Gd160', 3.18977e-06),
 ('Gd161', 8.5194e-07),
 ('Ho165', 1.03377726e-10),
 ('I127', 0.0),
 ('I128', 9.681748300000001e-09),
 ('I129', 0.004531414),
 ('I130', 2.11985e-06),
 ('I131', 0.0289069),
 ('I132', 9.13085e-05),
 ('I135', 0.0628187),
 ('In115', 0.000121551),
 ('Kr82', 4.2466880000000005e-09),
 ('Kr83', 0.00536203),
 ('Kr84', 0.0100192),
 ('Kr85', 0.00283404),
 ('Kr86', 0.0196497),
 ('La139', 0.0641343),
 ('La140', 5.21563e-05),
 ('Mo100', 0.0629233),
 ('Mo92', 0.0),
 ('Mo94', 2.99979e-14),
 ('Mo95', 1.389193165e-08),
 ('Mo96', 5.440152962e-06),
 ('Mo97', 0.059968),
 ('Mo98', 0.0578989),
 ('Mo99', 0.0610873),
 ('Nb95', 1.2940250079999999e-06),
 ('Nd142', 0.0),
 ('Nd143', 4.79966e-14),
 ('Nd144', 9.56932e-11),
 ('Nd145', 0.0393337),
 ('Nd146', 0.029969),
 ('Nd147', 0.0224673),
 ('Nd148', 0.0167354),
 ('Nd149', 0.0108162),
 ('Nd150', 0.00653249),
 ('Nd151', 0.00418124),
 ('Pd104', 0.0),
 ('Pd105', 0.0),
 ('Pd106', 0.0),
 ('Pd107', 0.00146192),
 ('Pd108', 0.000541252),
 ('Pd109', 0.000312199),
 ('Pm147', 2.48982e-11),
 ('Pm148', 4.44969e-11),
 ('Pm148_m1', 8.09943e-11),
 ('Pm149', 3.86973e-08),
 ('Pm150', 2.99979e-07),
 ('Pm151', 6.41955e-06),
 ('Pr141', 4.68967e-13),
 ('Pr142', 2.31484e-11),
 ('Pr143', 4.49968e-09),
 ('Pr144', 1.4299e-08),
 ('Rh102', 5.90958e-12),
 ('Rh102_m1', 4.72967e-12),
 ('Rh103', 6.37955e-13),
 ('Rh103_m1', 4.2697e-12),
 ('Rh104', 4.88965e-11),
 ('Rh105', 0.0),
 ('Rh105_m1', 0.0),
 ('Rh106', 0.0),
 ('Rh106_m1', 0.0),
 ('Ru100', 2.11985e-12),
 ('Ru101', 0.0517255),
 ('Ru102', 0.0429847),
 ('Ru103', 0.0303093),
 ('Ru104', 0.0188069),
 ('Ru105', 0.0096416),
 ('Ru106', 0.00401548),
 ('Sb121', 0.000130461),
 ('Sb123', 0.000156569),
 ('Sb125', 0.000340196),
 ('Sb127', 0.00156958),
 ('Sm147', 0.0),
 ('Sm148', 1.63988e-14),
 ('Sm149', 1.70988e-12),
 ('Sm150', 1.21991e-10),
 ('Sm151', 4.74966e-09),
 ('Sm152', 0.00266913),
 ('Sm153', 0.00158279),
 ('Sm154', 0.000744337),
 ('Sm155', 0.000321327),
 ('Sr89', 0.0473274),
 ('Sr90', 0.0578194),
 ('Tb159', 1.69988e-11),
 ('Tb160', 2.8398e-10),
 ('Tb161', 5.95958e-10),
 ('Tc100', 5.5896e-08),
 ('Tc99', 1.22991e-09),
 ('Tc99_m1', 2.8898e-10),
 ('Te127', 9.9193e-11),
 ('Te127_m1', 2.42983e-10),
 ('Te129_m1', 0.000902066),
 ('Te132', 0.042948),
 ('Xe128', 8.32941e-13),
 ('Xe130', 1.96986e-10),
 ('Xe131', 1.4199e-09),
 ('Xe132', 4.2197e-07),
 ('Xe133', 0.0669909),
 ('Xe134', 0.0787208),
 ('Xe135', 0.000785125),
 ('Xe135_m1', 0.00178122),
 ('Xe136', 0.0631272),
 ('Xe137', 0.0612832),
 ('Y89', 4.39969e-10),
 ('Y90', 4.48468e-08),
 ('Y91', 0.0582783),
 ('Zr90', 2.09485e-12),
 ('Zr91', 4.41969e-10),
 ('Zr92', 0.0602125),
 ('Zr93', 0.0634629),
 ('Zr94', 0.064722),
 ('Zr95', 0.0650274),
 ('Zr96', 0.0633924)]

In [11]:

chain_yields = defaultdict(float)
for nucname, y in thermal_yield.items():
    z, a, m = openmc.data.zam(nucname)
    chain_yields[a] += y
    
mass, yields = zip(*sorted(chain_yields.items()))

In [18]:

plt.plot(mass, yields)
plt.xlabel('Mass number')
plt.ylabel('Chain yield')

Out[18]:

Text(0, 0.5, 'Chain yield')

In [ ]: