17444981192

Committed 03 Sep 2025 08:14PM UTC coverage: 84.747%. First build

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Pull #3550

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Merge e2de1c407 into 591856472

Pull Request Pull Request #3550: [Point Detector] Add distribution get_pdf functionality

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/src/secondary_kalbach.cpp

#include "openmc/secondary_kalbach.h"

#include <algorithm> // for copy, move
#include <cmath>     // for log, sqrt, sinh
#include <cstddef>   // for size_t
#include <iterator>  // for back_inserter

#include "xtensor/xarray.hpp"
#include "xtensor/xview.hpp"

#include "openmc/hdf5_interface.h"
#include "openmc/random_dist.h"
#include "openmc/random_lcg.h"
#include "openmc/search.h"
#include "openmc/vector.h"

namespace openmc {

//==============================================================================
//! KalbachMann implementation
//==============================================================================

KalbachMann::KalbachMann(hid_t group)
{
  // Open incoming energy dataset
  hid_t dset = open_dataset(group, "energy");

  // Get interpolation parameters
  xt::xarray<int> temp;
  read_attribute(dset, "interpolation", temp);

  auto temp_b = xt::view(temp, 0); // view of breakpoints
  auto temp_i = xt::view(temp, 1); // view of interpolation parameters

  std::copy(temp_b.begin(), temp_b.end(), std::back_inserter(breakpoints_));
  for (const auto i : temp_i)
    interpolation_.push_back(int2interp(i));
  n_region_ = breakpoints_.size();

  // Get incoming energies
  read_dataset(dset, energy_);
  std::size_t n_energy = energy_.size();
  close_dataset(dset);

  // Get outgoing energy distribution data
  dset = open_dataset(group, "distribution");
  vector<int> offsets;
  vector<int> interp;
  vector<int> n_discrete;
  read_attribute(dset, "offsets", offsets);
  read_attribute(dset, "interpolation", interp);
  read_attribute(dset, "n_discrete_lines", n_discrete);

  xt::xarray<double> eout;
  read_dataset(dset, eout);
  close_dataset(dset);

  for (int i = 0; i < n_energy; ++i) {
    // Determine number of outgoing energies
    int j = offsets[i];
    int n;
    if (i < n_energy - 1) {
      n = offsets[i + 1] - j;
    } else {
      n = eout.shape()[1] - j;
    }

    // Assign interpolation scheme and number of discrete lines
    KMTable d;
    d.interpolation = int2interp(interp[i]);
    d.n_discrete = n_discrete[i];

    // Copy data
    d.e_out = xt::view(eout, 0, xt::range(j, j + n));
    d.p = xt::view(eout, 1, xt::range(j, j + n));
    d.c = xt::view(eout, 2, xt::range(j, j + n));
    d.r = xt::view(eout, 3, xt::range(j, j + n));
    d.a = xt::view(eout, 4, xt::range(j, j + n));

    // To get answers that match ACE data, for now we still use the tabulated
    // CDF values that were passed through to the HDF5 library. At a later
    // time, we can remove the CDF values from the HDF5 library and
    // reconstruct them using the PDF
    if (false) {
      // Calculate cumulative distribution function -- discrete portion
      for (int k = 0; k < d.n_discrete; ++k) {
        if (k == 0) {
          d.c[k] = d.p[k];
        } else {
          d.c[k] = d.c[k - 1] + d.p[k];
        }
      }

      // Continuous portion
      for (int k = d.n_discrete; k < n; ++k) {
        if (k == d.n_discrete) {
          d.c[k] = d.c[k - 1] + d.p[k];
        } else {
          if (d.interpolation == Interpolation::histogram) {
            d.c[k] = d.c[k - 1] + d.p[k - 1] * (d.e_out[k] - d.e_out[k - 1]);
          } else if (d.interpolation == Interpolation::lin_lin) {
            d.c[k] = d.c[k - 1] + 0.5 * (d.p[k - 1] + d.p[k]) *
                                    (d.e_out[k] - d.e_out[k - 1]);
          }
        }
      }

      // Normalize density and distribution functions
      d.p /= d.c[n - 1];
      d.c /= d.c[n - 1];
    }

    distribution_.push_back(std::move(d));
  } // incoming energies
}

void KalbachMann::sample(
  double E_in, double& E_out, double& mu, uint64_t* seed) const
{
  // Find energy bin and calculate interpolation factor -- if the energy is
  // outside the range of the tabulated energies, choose the first or last bins
  auto n_energy_in = energy_.size();
  int i;
  double r;
  if (E_in < energy_[0]) {
    i = 0;
    r = 0.0;
  } else if (E_in > energy_[n_energy_in - 1]) {
    i = n_energy_in - 2;
    r = 1.0;
  } else {
    i = lower_bound_index(energy_.begin(), energy_.end(), E_in);
    r = (E_in - energy_[i]) / (energy_[i + 1] - energy_[i]);
  }

  // Sample between the ith and [i+1]th bin
  int l = r > prn(seed) ? i + 1 : i;

  // Interpolation for energy E1 and EK
  int n_energy_out = distribution_[i].e_out.size();
  int n_discrete = distribution_[i].n_discrete;
  double E_i_1 = distribution_[i].e_out[n_discrete];
  double E_i_K = distribution_[i].e_out[n_energy_out - 1];

  n_energy_out = distribution_[i + 1].e_out.size();
  n_discrete = distribution_[i + 1].n_discrete;
  double E_i1_1 = distribution_[i + 1].e_out[n_discrete];
  double E_i1_K = distribution_[i + 1].e_out[n_energy_out - 1];

  double E_1 = E_i_1 + r * (E_i1_1 - E_i_1);
  double E_K = E_i_K + r * (E_i1_K - E_i_K);

  // Determine outgoing energy bin
  n_energy_out = distribution_[l].e_out.size();
  n_discrete = distribution_[l].n_discrete;
  double r1 = prn(seed);
  double c_k = distribution_[l].c[0];
  int k = 0;
  int end = n_energy_out - 2;

  // Discrete portion
  for (int j = 0; j < n_discrete; ++j) {
    k = j;
    c_k = distribution_[l].c[k];
    if (r1 < c_k) {
      end = j;
      break;
    }
  }

  // Continuous portion
  double c_k1;
  for (int j = n_discrete; j < end; ++j) {
    k = j;
    c_k1 = distribution_[l].c[k + 1];
    if (r1 < c_k1)
      break;
    k = j + 1;
    c_k = c_k1;
  }

  double E_l_k = distribution_[l].e_out[k];
  double p_l_k = distribution_[l].p[k];
  double km_r, km_a;
  if (distribution_[l].interpolation == Interpolation::histogram) {
    // Histogram interpolation
    if (p_l_k > 0.0 && k >= n_discrete) {
      E_out = E_l_k + (r1 - c_k) / p_l_k;
    } else {
      E_out = E_l_k;
    }

    // Determine Kalbach-Mann parameters
    km_r = distribution_[l].r[k];
    km_a = distribution_[l].a[k];

  } else {
    // Linear-linear interpolation
    double E_l_k1 = distribution_[l].e_out[k + 1];
    double p_l_k1 = distribution_[l].p[k + 1];

    double frac = (p_l_k1 - p_l_k) / (E_l_k1 - E_l_k);
    if (frac == 0.0) {
      E_out = E_l_k + (r1 - c_k) / p_l_k;
    } else {
      E_out =
        E_l_k +
        (std::sqrt(std::max(0.0, p_l_k * p_l_k + 2.0 * frac * (r1 - c_k))) -
          p_l_k) /
          frac;
    }

    // Determine Kalbach-Mann parameters
    km_r = distribution_[l].r[k] +
           (E_out - E_l_k) / (E_l_k1 - E_l_k) *
             (distribution_[l].r[k + 1] - distribution_[l].r[k]);
    km_a = distribution_[l].a[k] +
           (E_out - E_l_k) / (E_l_k1 - E_l_k) *
             (distribution_[l].a[k + 1] - distribution_[l].a[k]);
  }

  // Now interpolate between incident energy bins i and i + 1
  if (k >= n_discrete) {
    if (l == i) {
      E_out = E_1 + (E_out - E_i_1) * (E_K - E_1) / (E_i_K - E_i_1);
    } else {
      E_out = E_1 + (E_out - E_i1_1) * (E_K - E_1) / (E_i1_K - E_i1_1);
    }
  }

  // Sampled correlated angle from Kalbach-Mann parameters
  if (prn(seed) > km_r) {
    double T = uniform_distribution(-1., 1., seed) * std::sinh(km_a);
    mu = std::log(T + std::sqrt(T * T + 1.0)) / km_a;
  } else {
    double r1 = prn(seed);
    mu = std::log(r1 * std::exp(km_a) + (1.0 - r1) * std::exp(-km_a)) / km_a;
  }
}
double KalbachMann::get_pdf(
  double E_in, double mu, double& E_out, uint64_t* seed) const
{
  // Find energy bin and calculate interpolation factor -- if the energy is
  // outside the range of the tabulated energies, choose the first or last bins

  // double E_out;
  auto n_energy_in = energy_.size();
  int i;
  double r;
  if (E_in < energy_[0]) {
    i = 0;
    r = 0.0;
  } else if (E_in > energy_[n_energy_in - 1]) {
    i = n_energy_in - 2;
    r = 1.0;
  } else {
    i = lower_bound_index(energy_.begin(), energy_.end(), E_in);
    r = (E_in - energy_[i]) / (energy_[i + 1] - energy_[i]);
  }

  // Sample between the ith and [i+1]th bin
  int l = r > prn(seed) ? i + 1 : i;

  // Interpolation for energy E1 and EK
  int n_energy_out = distribution_[i].e_out.size();
  int n_discrete = distribution_[i].n_discrete;
  double E_i_1 = distribution_[i].e_out[n_discrete];
  double E_i_K = distribution_[i].e_out[n_energy_out - 1];

  n_energy_out = distribution_[i + 1].e_out.size();
  n_discrete = distribution_[i + 1].n_discrete;
  double E_i1_1 = distribution_[i + 1].e_out[n_discrete];
  double E_i1_K = distribution_[i + 1].e_out[n_energy_out - 1];

  double E_1 = E_i_1 + r * (E_i1_1 - E_i_1);
  double E_K = E_i_K + r * (E_i1_K - E_i_K);

  // Determine outgoing energy bin
  n_energy_out = distribution_[l].e_out.size();
  n_discrete = distribution_[l].n_discrete;
  double r1 = prn(seed);
  double c_k = distribution_[l].c[0];
  int k = 0;
  int end = n_energy_out - 2;

  // Discrete portion
  for (int j = 0; j < n_discrete; ++j) {
    k = j;
    c_k = distribution_[l].c[k];
    if (r1 < c_k) {
      end = j;
      break;
    }
  }

  // Continuous portion
  double c_k1;
  for (int j = n_discrete; j < end; ++j) {
    k = j;
    c_k1 = distribution_[l].c[k + 1];
    if (r1 < c_k1)
      break;
    k = j + 1;
    c_k = c_k1;
  }

  double E_l_k = distribution_[l].e_out[k];
  double p_l_k = distribution_[l].p[k];
  double km_r, km_a;
  if (distribution_[l].interpolation == Interpolation::histogram) {
    // Histogram interpolation
    if (p_l_k > 0.0 && k >= n_discrete) {
      E_out = E_l_k + (r1 - c_k) / p_l_k;
    } else {
      E_out = E_l_k;
    }
    // Determine Kalbach-Mann parameters
    km_r = distribution_[l].r[k];
    km_a = distribution_[l].a[k];

  } else {
    // Linear-linear interpolation
    double E_l_k1 = distribution_[l].e_out[k + 1];
    double p_l_k1 = distribution_[l].p[k + 1];

    double frac = (p_l_k1 - p_l_k) / (E_l_k1 - E_l_k);
    if (frac == 0.0) {
      E_out = E_l_k + (r1 - c_k) / p_l_k;
    } else {
      E_out =
        E_l_k +
        (std::sqrt(std::max(0.0, p_l_k * p_l_k + 2.0 * frac * (r1 - c_k))) -
          p_l_k) /
          frac;
    }
    //  Linear-linear interpolation
    // Determine Kalbach-Mann parameters
    km_r = distribution_[l].r[k] +
           (E_out - E_l_k) / (E_l_k1 - E_l_k) *
             (distribution_[l].r[k + 1] - distribution_[l].r[k]);
    km_a = distribution_[l].a[k] +
           (E_out - E_l_k) / (E_l_k1 - E_l_k) *
             (distribution_[l].a[k + 1] - distribution_[l].a[k]);
  }

  // Now interpolate between incident energy bins i and i + 1
  if (k >= n_discrete) {
    if (l == i) {
      E_out = E_1 + (E_out - E_i_1) * (E_K - E_1) / (E_i_K - E_i_1);
    } else {
      E_out = E_1 + (E_out - E_i1_1) * (E_K - E_1) / (E_i1_K - E_i1_1);
    }
  }

  // https://docs.openmc.org/en/latest/methods/neutron_physics.html#equation-KM-pdf-angle
  double pdf = km_a / (2 * std::sinh(km_a)) *
               (std::cosh(km_a * mu) + km_r * std::sinh(km_a * mu));

  return pdf;
}

} // namespace openmc

1	#include "openmc/secondary_kalbach.h"
2
3	#include <algorithm> // for copy, move
4	#include <cmath> // for log, sqrt, sinh
5	#include <cstddef> // for size_t
6	#include <iterator> // for back_inserter
7
8	#include "xtensor/xarray.hpp"
9	#include "xtensor/xview.hpp"
10
11	#include "openmc/hdf5_interface.h"
12	#include "openmc/random_dist.h"
13	#include "openmc/random_lcg.h"
14	#include "openmc/search.h"
15	#include "openmc/vector.h"
16
17	namespace openmc {
18
19	//==============================================================================
20	//! KalbachMann implementation
21	//==============================================================================
22
23	KalbachMann::KalbachMann(hid_t group)	63,343✔
24	{
25	// Open incoming energy dataset
26	hid_t dset = open_dataset(group, "energy");	63,343✔
27
28	// Get interpolation parameters
29	xt::xarray<int> temp;	63,343✔
30	read_attribute(dset, "interpolation", temp);	63,343✔
31
32	auto temp_b = xt::view(temp, 0); // view of breakpoints	63,343✔
33	auto temp_i = xt::view(temp, 1); // view of interpolation parameters	63,343✔
34
35	std::copy(temp_b.begin(), temp_b.end(), std::back_inserter(breakpoints_));	63,343✔
36	for (const auto i : temp_i)	126,686✔
37	interpolation_.push_back(int2interp(i));	63,343✔
38	n_region_ = breakpoints_.size();	63,343✔
39
40	// Get incoming energies
41	read_dataset(dset, energy_);	63,343✔
42	std::size_t n_energy = energy_.size();	63,343✔
43	close_dataset(dset);	63,343✔
44
45	// Get outgoing energy distribution data
46	dset = open_dataset(group, "distribution");	63,343✔
47	vector<int> offsets;	63,343✔
48	vector<int> interp;	63,343✔
49	vector<int> n_discrete;	63,343✔
50	read_attribute(dset, "offsets", offsets);	63,343✔
51	read_attribute(dset, "interpolation", interp);	63,343✔
52	read_attribute(dset, "n_discrete_lines", n_discrete);	63,343✔
53
54	xt::xarray<double> eout;	63,343✔
55	read_dataset(dset, eout);	63,343✔
56	close_dataset(dset);	63,343✔
57
58	for (int i = 0; i < n_energy; ++i) {	1,291,531✔
59	// Determine number of outgoing energies
60	int j = offsets[i];	1,228,188✔
61	int n;
62	if (i < n_energy - 1) {	1,228,188✔
63	n = offsets[i + 1] - j;	1,164,845✔
64	} else {
65	n = eout.shape()[1] - j;	63,343✔
66	}
67
68	// Assign interpolation scheme and number of discrete lines
69	KMTable d;	1,228,188✔
70	d.interpolation = int2interp(interp[i]);	1,228,188✔
71	d.n_discrete = n_discrete[i];	1,228,188✔
72
73	// Copy data
74	d.e_out = xt::view(eout, 0, xt::range(j, j + n));	1,228,188✔
75	d.p = xt::view(eout, 1, xt::range(j, j + n));	1,228,188✔
76	d.c = xt::view(eout, 2, xt::range(j, j + n));	1,228,188✔
77	d.r = xt::view(eout, 3, xt::range(j, j + n));	1,228,188✔
78	d.a = xt::view(eout, 4, xt::range(j, j + n));	1,228,188✔
79
80	// To get answers that match ACE data, for now we still use the tabulated
81	// CDF values that were passed through to the HDF5 library. At a later
82	// time, we can remove the CDF values from the HDF5 library and
83	// reconstruct them using the PDF
84	if (false) {
85	// Calculate cumulative distribution function -- discrete portion
86	for (int k = 0; k < d.n_discrete; ++k) {
87	if (k == 0) {
88	d.c[k] = d.p[k];
89	} else {
90	d.c[k] = d.c[k - 1] + d.p[k];
91	}
92	}
93
94	// Continuous portion
95	for (int k = d.n_discrete; k < n; ++k) {
96	if (k == d.n_discrete) {
97	d.c[k] = d.c[k - 1] + d.p[k];
98	} else {
99	if (d.interpolation == Interpolation::histogram) {
100	d.c[k] = d.c[k - 1] + d.p[k - 1] * (d.e_out[k] - d.e_out[k - 1]);
101	} else if (d.interpolation == Interpolation::lin_lin) {
102	d.c[k] = d.c[k - 1] + 0.5 * (d.p[k - 1] + d.p[k]) *
103	(d.e_out[k] - d.e_out[k - 1]);
104	}
105	}
106	}
107
108	// Normalize density and distribution functions
109	d.p /= d.c[n - 1];
110	d.c /= d.c[n - 1];
111	}
112
113	distribution_.push_back(std::move(d));	1,228,188✔
114	} // incoming energies	1,228,188✔
115	}	63,343✔
116
117	void KalbachMann::sample(	3,239,745✔
118	double E_in, double& E_out, double& mu, uint64_t* seed) const
119	{
120	// Find energy bin and calculate interpolation factor -- if the energy is
121	// outside the range of the tabulated energies, choose the first or last bins
122	auto n_energy_in = energy_.size();	3,239,745✔
123	int i;
124	double r;
125	if (E_in < energy_[0]) {	3,239,745✔
126	i = 0;	×
127	r = 0.0;	×
128	} else if (E_in > energy_[n_energy_in - 1]) {	3,239,745✔
129	i = n_energy_in - 2;	×
130	r = 1.0;	×
131	} else {
132	i = lower_bound_index(energy_.begin(), energy_.end(), E_in);	3,239,745✔
133	r = (E_in - energy_[i]) / (energy_[i + 1] - energy_[i]);	3,239,745✔
134	}
135
136	// Sample between the ith and [i+1]th bin
137	int l = r > prn(seed) ? i + 1 : i;	3,239,745✔
138
139	// Interpolation for energy E1 and EK
140	int n_energy_out = distribution_[i].e_out.size();	3,239,745✔
141	int n_discrete = distribution_[i].n_discrete;	3,239,745✔
142	double E_i_1 = distribution_[i].e_out[n_discrete];	3,239,745✔
143	double E_i_K = distribution_[i].e_out[n_energy_out - 1];	3,239,745✔
144
145	n_energy_out = distribution_[i + 1].e_out.size();	3,239,745✔
146	n_discrete = distribution_[i + 1].n_discrete;	3,239,745✔
147	double E_i1_1 = distribution_[i + 1].e_out[n_discrete];	3,239,745✔
148	double E_i1_K = distribution_[i + 1].e_out[n_energy_out - 1];	3,239,745✔
149
150	double E_1 = E_i_1 + r * (E_i1_1 - E_i_1);	3,239,745✔
151	double E_K = E_i_K + r * (E_i1_K - E_i_K);	3,239,745✔
152
153	// Determine outgoing energy bin
154	n_energy_out = distribution_[l].e_out.size();	3,239,745✔
155	n_discrete = distribution_[l].n_discrete;	3,239,745✔
156	double r1 = prn(seed);	3,239,745✔
157	double c_k = distribution_[l].c[0];	3,239,745✔
158	int k = 0;	3,239,745✔
159	int end = n_energy_out - 2;	3,239,745✔
160
161	// Discrete portion
162	for (int j = 0; j < n_discrete; ++j) {	3,239,745✔
163	k = j;	×
164	c_k = distribution_[l].c[k];	×
165	if (r1 < c_k) {	×
166	end = j;	×
167	break;	×
168	}
169	}
170
171	// Continuous portion
172	double c_k1;
173	for (int j = n_discrete; j < end; ++j) {	89,162,654✔
174	k = j;	89,053,956✔
175	c_k1 = distribution_[l].c[k + 1];	89,053,956✔
176	if (r1 < c_k1)	89,053,956✔
177	break;	3,131,047✔
178	k = j + 1;	85,922,909✔
179	c_k = c_k1;	85,922,909✔
180	}
181
182	double E_l_k = distribution_[l].e_out[k];	3,239,745✔
183	double p_l_k = distribution_[l].p[k];	3,239,745✔
184	double km_r, km_a;
185	if (distribution_[l].interpolation == Interpolation::histogram) {	3,239,745✔
186	// Histogram interpolation
187	if (p_l_k > 0.0 && k >= n_discrete) {	3,219,417✔
188	E_out = E_l_k + (r1 - c_k) / p_l_k;	3,219,417✔
189	} else {
190	E_out = E_l_k;	×
191	}
192
193	// Determine Kalbach-Mann parameters
194	km_r = distribution_[l].r[k];	3,219,417✔
195	km_a = distribution_[l].a[k];	3,219,417✔
196
197	} else {
198	// Linear-linear interpolation
199	double E_l_k1 = distribution_[l].e_out[k + 1];	20,328✔
200	double p_l_k1 = distribution_[l].p[k + 1];	20,328✔
201
202	double frac = (p_l_k1 - p_l_k) / (E_l_k1 - E_l_k);	20,328✔
203	if (frac == 0.0) {	20,328✔
204	E_out = E_l_k + (r1 - c_k) / p_l_k;	×
205	} else {
206	E_out =	20,328✔
207	E_l_k +	20,328✔
208	(std::sqrt(std::max(0.0, p_l_k * p_l_k + 2.0 * frac * (r1 - c_k))) -	20,328✔
209	p_l_k) /	20,328✔
210	frac;
211	}
212
213	// Determine Kalbach-Mann parameters
214	km_r = distribution_[l].r[k] +	20,328✔
215	(E_out - E_l_k) / (E_l_k1 - E_l_k) *	40,656✔
216	(distribution_[l].r[k + 1] - distribution_[l].r[k]);	20,328✔
217	km_a = distribution_[l].a[k] +	20,328✔
218	(E_out - E_l_k) / (E_l_k1 - E_l_k) *	40,656✔
219	(distribution_[l].a[k + 1] - distribution_[l].a[k]);	20,328✔
220	}
221
222	// Now interpolate between incident energy bins i and i + 1
223	if (k >= n_discrete) {	3,239,745✔
224	if (l == i) {	3,239,745✔
225	E_out = E_1 + (E_out - E_i_1) * (E_K - E_1) / (E_i_K - E_i_1);	1,618,810✔
226	} else {
227	E_out = E_1 + (E_out - E_i1_1) * (E_K - E_1) / (E_i1_K - E_i1_1);	1,620,935✔
228	}
229	}
230
231	// Sampled correlated angle from Kalbach-Mann parameters
232	if (prn(seed) > km_r) {	3,239,745✔
233	double T = uniform_distribution(-1., 1., seed) * std::sinh(km_a);	3,170,588✔
234	mu = std::log(T + std::sqrt(T * T + 1.0)) / km_a;	3,170,588✔
235	} else {
236	double r1 = prn(seed);	69,157✔
237	mu = std::log(r1 * std::exp(km_a) + (1.0 - r1) * std::exp(-km_a)) / km_a;	69,157✔
238	}
239	}	3,239,745✔
NEW 240	double KalbachMann::get_pdf(	×
241	double E_in, double mu, double& E_out, uint64_t* seed) const
242	{
243	// Find energy bin and calculate interpolation factor -- if the energy is
244	// outside the range of the tabulated energies, choose the first or last bins
245
246	// double E_out;
NEW 247	auto n_energy_in = energy_.size();	×
248	int i;
249	double r;
NEW 250	if (E_in < energy_[0]) {	×
NEW 251	i = 0;	×
NEW 252	r = 0.0;	×
NEW 253	} else if (E_in > energy_[n_energy_in - 1]) {	×
NEW 254	i = n_energy_in - 2;	×
NEW 255	r = 1.0;	×
256	} else {
NEW 257	i = lower_bound_index(energy_.begin(), energy_.end(), E_in);	×
NEW 258	r = (E_in - energy_[i]) / (energy_[i + 1] - energy_[i]);	×
259	}
260
261	// Sample between the ith and [i+1]th bin
NEW 262	int l = r > prn(seed) ? i + 1 : i;	×
263
264	// Interpolation for energy E1 and EK
NEW 265	int n_energy_out = distribution_[i].e_out.size();	×
NEW 266	int n_discrete = distribution_[i].n_discrete;	×
NEW 267	double E_i_1 = distribution_[i].e_out[n_discrete];	×
NEW 268	double E_i_K = distribution_[i].e_out[n_energy_out - 1];	×
269
NEW 270	n_energy_out = distribution_[i + 1].e_out.size();	×
NEW 271	n_discrete = distribution_[i + 1].n_discrete;	×
NEW 272	double E_i1_1 = distribution_[i + 1].e_out[n_discrete];	×
NEW 273	double E_i1_K = distribution_[i + 1].e_out[n_energy_out - 1];	×
274
NEW 275	double E_1 = E_i_1 + r * (E_i1_1 - E_i_1);	×
NEW 276	double E_K = E_i_K + r * (E_i1_K - E_i_K);	×
277
278	// Determine outgoing energy bin
NEW 279	n_energy_out = distribution_[l].e_out.size();	×
NEW 280	n_discrete = distribution_[l].n_discrete;	×
NEW 281	double r1 = prn(seed);	×
NEW 282	double c_k = distribution_[l].c[0];	×
NEW 283	int k = 0;	×
NEW 284	int end = n_energy_out - 2;	×
285
286	// Discrete portion
NEW 287	for (int j = 0; j < n_discrete; ++j) {	×
NEW 288	k = j;	×
NEW 289	c_k = distribution_[l].c[k];	×
NEW 290	if (r1 < c_k) {	×
NEW 291	end = j;	×
NEW 292	break;	×
293	}
294	}
295
296	// Continuous portion
297	double c_k1;
NEW 298	for (int j = n_discrete; j < end; ++j) {	×
NEW 299	k = j;	×
NEW 300	c_k1 = distribution_[l].c[k + 1];	×
NEW 301	if (r1 < c_k1)	×
NEW 302	break;	×
NEW 303	k = j + 1;	×
NEW 304	c_k = c_k1;	×
305	}
306
NEW 307	double E_l_k = distribution_[l].e_out[k];	×
NEW 308	double p_l_k = distribution_[l].p[k];	×
309	double km_r, km_a;
NEW 310	if (distribution_[l].interpolation == Interpolation::histogram) {	×
311	// Histogram interpolation
NEW 312	if (p_l_k > 0.0 && k >= n_discrete) {	×
NEW 313	E_out = E_l_k + (r1 - c_k) / p_l_k;	×
314	} else {
NEW 315	E_out = E_l_k;	×
316	}
317	// Determine Kalbach-Mann parameters
NEW 318	km_r = distribution_[l].r[k];	×
NEW 319	km_a = distribution_[l].a[k];	×
320
321	} else {
322	// Linear-linear interpolation
NEW 323	double E_l_k1 = distribution_[l].e_out[k + 1];	×
NEW 324	double p_l_k1 = distribution_[l].p[k + 1];	×
325
NEW 326	double frac = (p_l_k1 - p_l_k) / (E_l_k1 - E_l_k);	×
NEW 327	if (frac == 0.0) {	×
NEW 328	E_out = E_l_k + (r1 - c_k) / p_l_k;	×
329	} else {
NEW 330	E_out =	×
NEW 331	E_l_k +	×
NEW 332	(std::sqrt(std::max(0.0, p_l_k * p_l_k + 2.0 * frac * (r1 - c_k))) -	×
NEW 333	p_l_k) /	×
334	frac;
335	}
336	// Linear-linear interpolation
337	// Determine Kalbach-Mann parameters
NEW 338	km_r = distribution_[l].r[k] +	×
NEW 339	(E_out - E_l_k) / (E_l_k1 - E_l_k) *	×
NEW 340	(distribution_[l].r[k + 1] - distribution_[l].r[k]);	×
NEW 341	km_a = distribution_[l].a[k] +	×
NEW 342	(E_out - E_l_k) / (E_l_k1 - E_l_k) *	×
NEW 343	(distribution_[l].a[k + 1] - distribution_[l].a[k]);	×
344	}
345
346	// Now interpolate between incident energy bins i and i + 1
NEW 347	if (k >= n_discrete) {	×
NEW 348	if (l == i) {	×
NEW 349	E_out = E_1 + (E_out - E_i_1) * (E_K - E_1) / (E_i_K - E_i_1);	×
350	} else {
NEW 351	E_out = E_1 + (E_out - E_i1_1) * (E_K - E_1) / (E_i1_K - E_i1_1);	×
352	}
353	}
354
355	// https://docs.openmc.org/en/latest/methods/neutron_physics.html#equation-KM-pdf-angle
NEW 356	double pdf = km_a / (2 * std::sinh(km_a)) *	×
NEW 357	(std::cosh(km_a * mu) + km_r * std::sinh(km_a * mu));	×
358
NEW 359	return pdf;	×
360	}
361
362	} // namespace openmc

openmc-dev / openmc / 17444981192

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