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Doctors the incoherent inelastic TSL data when in continuous format.

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This commit is contained in:
Hunter Belanger 2022-11-03 18:55:06 +01:00
parent 3682c02d1f
commit fd516c1c4c
1 changed files with 29 additions and 0 deletions
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29
openmc/data/thermal.py
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@ -670,12 +670,41 @@ class ThermalScattering(EqualityMixin):
mu_i = []
for j in range(n_energy_out[i]):
mu = ace.xss[idx + 4:idx + 4 + n_mu]
# The equiprobable angles produced by NJOY are not always
# sorted. This is problematic when the smearing algorithm
# is applied when sampling the angles. We sort the angles
# here, because they are equiprobable, so the order
# doesn't mater.
mu.sort()
p_mu = 1. / n_mu * np.ones(n_mu)
mu_ij = Discrete(mu, p_mu)
mu_ij.c = np.cumsum(p_mu)
mu_i.append(mu_ij)
idx += 3 + n_mu
# Check if the CDF for the outgoing energy distribution starts
# at 0. For NJOY and FRENDY evaluations, this is never the case,
# and can very rarely lead to negative energies when sampling
# the outgoing energy. From Eq. 7.6 of the ENDF manual, we can
# add the outgoing energy 0 eV, which has a PDF of 0 (and of
# course, a CDF of 0 as well).
if eout_i.c[0] > 0.:
eout_i.x = np.insert(eout_i.x, 0, 0.)
eout_i.p = np.insert(eout_i.p, 0, 0.)
eout_i.c = np.insert(eout_i.c, 0, 0.)
# For this added outgoing energy (of 0 eV) we add a set of
# isotropic discrete angles.
dmu = 2. / n_mu
mu = np.linsace(-1. + 0.5*dmu, 1. - 0.5*dmu, n_mu)
p_mu = 1. / n_mu * np.ones(n_mu)
mu_0 = Discrete(mu, p_mu)
mu_0.c = np.cumsum(p_mu)
mu_i.insert(0, mu_0)
# We don't worry about renormalizing the outgoing energy PDF/CDF
# after this manipulation, because it never seems to be
# normalized to begin with (at least with NJOY).
energy_out.append(eout_i)
mu_out.append(mu_i)