From a8171cbd4e9a1ee801a52f6f0c1426982b73774f Mon Sep 17 00:00:00 2001 From: Ethan Krammer <68677905+ethankrammer@users.noreply.github.com> Date: Thu, 27 Jun 2024 09:22:10 -0500 Subject: [PATCH 1/3] Implementation of Shannon Entropy for Random Ray (#3030) Co-authored-by: Ethan Krammer Co-authored-by: John Tramm --- docs/source/methods/eigenvalue.rst | 17 +++- docs/source/methods/random_ray.rst | 36 +++++++ docs/source/usersguide/random_ray.rst | 11 +++ src/eigenvalue.cpp | 2 +- src/random_ray/flat_source_domain.cpp | 38 +++++++- src/settings.cpp | 45 +++++---- src/simulation.cpp | 3 +- .../random_ray_entropy/__init__.py | 0 .../random_ray_entropy/geometry.xml | 88 ++++++++++++++++++ .../random_ray_entropy/materials.xml | 8 ++ .../random_ray_entropy/mgxs.h5 | Bin 0 -> 10664 bytes .../random_ray_entropy/results_true.dat | 13 +++ .../random_ray_entropy/settings.xml | 17 ++++ .../random_ray_entropy/test.py | 33 +++++++ 14 files changed, 282 insertions(+), 29 deletions(-) create mode 100644 tests/regression_tests/random_ray_entropy/__init__.py create mode 100644 tests/regression_tests/random_ray_entropy/geometry.xml create mode 100644 tests/regression_tests/random_ray_entropy/materials.xml create mode 100644 tests/regression_tests/random_ray_entropy/mgxs.h5 create mode 100644 tests/regression_tests/random_ray_entropy/results_true.dat create mode 100644 tests/regression_tests/random_ray_entropy/settings.xml create mode 100644 tests/regression_tests/random_ray_entropy/test.py diff --git a/docs/source/methods/eigenvalue.rst b/docs/source/methods/eigenvalue.rst index b63723c0264..8abcc09574b 100644 --- a/docs/source/methods/eigenvalue.rst +++ b/docs/source/methods/eigenvalue.rst @@ -55,15 +55,17 @@ in :ref:`fission-bank-algorithms`. Source Convergence Issues ------------------------- +.. _methods-shannon-entropy: + Diagnosing Convergence with Shannon Entropy ------------------------------------------- As discussed earlier, it is necessary to converge both :math:`k_{eff}` and the source distribution before any tallies can begin. Moreover, the convergence rate -of the source distribution is in general slower than that of -:math:`k_{eff}`. One should thus examine not only the convergence of -:math:`k_{eff}` but also the convergence of the source distribution in order to -make decisions on when to start active batches. +of the source distribution is in general slower than that of :math:`k_{eff}`. +One should thus examine not only the convergence of :math:`k_{eff}` but also the +convergence of the source distribution in order to make decisions on when to +start active batches. However, the representation of the source distribution makes it a bit more difficult to analyze its convergence. Since :math:`k_{eff}` is a scalar @@ -108,6 +110,13 @@ at plots of :math:`k_{eff}` and the Shannon entropy. A number of methods have been proposed (see e.g. [Romano]_, [Ueki]_), but each of these is not without problems. +Shannon entropy is calculated differently for the random ray solver, as +described :ref:`in the random ray theory section +`. Additionally, as the Shannon entropy only +serves as a diagnostic tool for convergence of the fission source distribution, +there is currently no diagnostic to determine if the scattering source +distribution in random ray is converged. + --------------------------- Uniform Fission Site Method --------------------------- diff --git a/docs/source/methods/random_ray.rst b/docs/source/methods/random_ray.rst index 427ba11489f..d46d3ad4165 100644 --- a/docs/source/methods/random_ray.rst +++ b/docs/source/methods/random_ray.rst @@ -411,6 +411,8 @@ which when partially simplified becomes: Note that there are now four (seemingly identical) volume terms in this equation. +.. _methods-volume-dilemma: + ~~~~~~~~~~~~~~ Volume Dilemma ~~~~~~~~~~~~~~ @@ -745,6 +747,7 @@ How are Tallies Handled? Most tallies, filters, and scores that you would expect to work with a multigroup solver like random ray should work. For example, you can define 3D mesh tallies with energy filters and flux, fission, and nu-fission scores, etc. + There are some restrictions though. For starters, it is assumed that all filter mesh boundaries will conform to physical surface boundaries (or lattice boundaries) in the simulation geometry. It is acceptable for multiple cells @@ -754,6 +757,39 @@ behavior if a single simulation cell is able to score to multiple filter mesh cells. In the future, the capability to fully support mesh tallies may be added to OpenMC, but for now this restriction needs to be respected. +.. _methods-shannon-entropy-random-ray: + +----------------------------- +Shannon Entropy in Random Ray +----------------------------- + +As :math:`k_{eff}` is updated at each generation, the fission source at each FSR +is used to compute the Shannon entropy. This follows the :ref:`same procedure +for computing Shannon entropy in continuous-energy or multigroup Monte Carlo +simulations `, except that fission sources at FSRs are +considered, rather than fission sites of user-defined regular meshes. Thus, the +volume-weighted fission rate is considered instead, and the fraction of fission +sources is adjusted such that: + +.. math:: + :label: fraction-source-random-ray + + S_i = \frac{\text{Fission source in FSR $i \times$ Volume of FSR + $i$}}{\text{Total fission source}} = \frac{Q_{i} V_{i}}{\sum_{i=1}^{i=N} + Q_{i} V_{i}} + +The Shannon entropy is then computed normally as + +.. math:: + :label: shannon-entropy-random-ray + + H = - \sum_{i=1}^N S_i \log_2 S_i + +where :math:`N` is the number of FSRs. FSRs with no fission source (or, +occassionally, negative fission source, :ref:`due to the volume estimator +problem `) are skipped to avoid taking an undefined +logarithm in :eq:`shannon-entropy-random-ray`. + .. _usersguide_fixed_source_methods: ------------ diff --git a/docs/source/usersguide/random_ray.rst b/docs/source/usersguide/random_ray.rst index 61f0746500c..2a038b12257 100644 --- a/docs/source/usersguide/random_ray.rst +++ b/docs/source/usersguide/random_ray.rst @@ -62,6 +62,17 @@ solver:: settings.batches = 1200 settings.inactive = 600 +--------------- +Shannon Entropy +--------------- + +Similar to Monte Carlo, :ref:`Shannon entropy +` can be used to gauge whether the fission +source has fully developed. The Shannon entropy is calculated automatically +after each batch and is printed to the statepoint file. Unlike Monte Carlo, an +entropy mesh does not need to be defined, as the Shannon entropy is calculated +over FSRs using a volume-weighted approach. + ------------------------------- Inactive Ray Length (Dead Zone) ------------------------------- diff --git a/src/eigenvalue.cpp b/src/eigenvalue.cpp index d5410094b18..8669d76f947 100644 --- a/src/eigenvalue.cpp +++ b/src/eigenvalue.cpp @@ -556,7 +556,7 @@ void shannon_entropy() double H = 0.0; for (auto p_i : p) { if (p_i > 0.0) { - H -= p_i * std::log(p_i) / std::log(2.0); + H -= p_i * std::log2(p_i); } } diff --git a/src/random_ray/flat_source_domain.cpp b/src/random_ray/flat_source_domain.cpp index 7f5d76943e5..792e97da0c1 100644 --- a/src/random_ray/flat_source_domain.cpp +++ b/src/random_ray/flat_source_domain.cpp @@ -1,6 +1,7 @@ #include "openmc/random_ray/flat_source_domain.h" #include "openmc/cell.h" +#include "openmc/eigenvalue.h" #include "openmc/geometry.h" #include "openmc/material.h" #include "openmc/message_passing.h" @@ -278,6 +279,9 @@ double FlatSourceDomain::compute_k_eff(double k_eff_old) const const int t = 0; const int a = 0; + // Vector for gathering fission source terms for Shannon entropy calculation + vector p(n_source_regions_, 0.0f); + #pragma omp parallel for reduction(+ : fission_rate_old, fission_rate_new) for (int sr = 0; sr < n_source_regions_; sr++) { @@ -300,12 +304,38 @@ double FlatSourceDomain::compute_k_eff(double k_eff_old) const sr_fission_source_new += nu_sigma_f * scalar_flux_new_[idx]; } - fission_rate_old += sr_fission_source_old * volume; - fission_rate_new += sr_fission_source_new * volume; + // Compute total fission rates in FSR + sr_fission_source_old *= volume; + sr_fission_source_new *= volume; + + // Accumulate totals + fission_rate_old += sr_fission_source_old; + fission_rate_new += sr_fission_source_new; + + // Store total fission rate in the FSR for Shannon calculation + p[sr] = sr_fission_source_new; } double k_eff_new = k_eff_old * (fission_rate_new / fission_rate_old); + double H = 0.0; + // defining an inverse sum for better performance + double inverse_sum = 1 / fission_rate_new; + +#pragma omp parallel for reduction(+ : H) + for (int sr = 0; sr < n_source_regions_; sr++) { + // Only if FSR has non-negative and non-zero fission source + if (p[sr] > 0.0f) { + // Normalize to total weight of bank sites. p_i for better performance + float p_i = p[sr] * inverse_sum; + // Sum values to obtain Shannon entropy. + H -= p_i * std::log2(p_i); + } + } + + // Adds entropy value to shared entropy vector in openmc namespace. + simulation::entropy.push_back(H); + return k_eff_new; } @@ -525,8 +555,8 @@ void FlatSourceDomain::random_ray_tally() #pragma omp atomic tally.results_(task.filter_idx, task.score_idx, TallyResult::VALUE) += score; - } // end tally task loop - } // end energy group loop + } + } // For flux tallies, the total volume of the spatial region is needed // for normalizing the flux. We store this volume in a separate tensor. diff --git a/src/settings.cpp b/src/settings.cpp index 6c3226b04a6..4ffa50cdf45 100644 --- a/src/settings.cpp +++ b/src/settings.cpp @@ -627,30 +627,37 @@ void read_settings_xml(pugi::xml_node root) } } - // Shannon Entropy mesh - if (check_for_node(root, "entropy_mesh")) { - int temp = std::stoi(get_node_value(root, "entropy_mesh")); - if (model::mesh_map.find(temp) == model::mesh_map.end()) { - fatal_error(fmt::format( - "Mesh {} specified for Shannon entropy does not exist.", temp)); + // Shannon entropy + if (solver_type == SolverType::RANDOM_RAY) { + if (check_for_node(root, "entropy_mesh")) { + fatal_error("Random ray uses FSRs to compute the Shannon entropy. " + "No user-defined entropy mesh is supported."); } + entropy_on = true; + } else if (solver_type == SolverType::MONTE_CARLO) { + if (check_for_node(root, "entropy_mesh")) { + int temp = std::stoi(get_node_value(root, "entropy_mesh")); + if (model::mesh_map.find(temp) == model::mesh_map.end()) { + fatal_error(fmt::format( + "Mesh {} specified for Shannon entropy does not exist.", temp)); + } - auto* m = - dynamic_cast(model::meshes[model::mesh_map.at(temp)].get()); - if (!m) - fatal_error("Only regular meshes can be used as an entropy mesh"); - simulation::entropy_mesh = m; + auto* m = dynamic_cast( + model::meshes[model::mesh_map.at(temp)].get()); + if (!m) + fatal_error("Only regular meshes can be used as an entropy mesh"); + simulation::entropy_mesh = m; - // Turn on Shannon entropy calculation - entropy_on = true; + // Turn on Shannon entropy calculation + entropy_on = true; - } else if (check_for_node(root, "entropy")) { - fatal_error( - "Specifying a Shannon entropy mesh via the element " - "is deprecated. Please create a mesh using and then reference " - "it by specifying its ID in an element."); + } else if (check_for_node(root, "entropy")) { + fatal_error( + "Specifying a Shannon entropy mesh via the element " + "is deprecated. Please create a mesh using and then reference " + "it by specifying its ID in an element."); + } } - // Uniform fission source weighting mesh if (check_for_node(root, "ufs_mesh")) { auto temp = std::stoi(get_node_value(root, "ufs_mesh")); diff --git a/src/simulation.cpp b/src/simulation.cpp index 2d5d75aa477..be03e48553c 100644 --- a/src/simulation.cpp +++ b/src/simulation.cpp @@ -531,7 +531,8 @@ void finalize_generation() if (settings::run_mode == RunMode::EIGENVALUE) { // Calculate shannon entropy - if (settings::entropy_on) + if (settings::entropy_on && + settings::solver_type == SolverType::MONTE_CARLO) shannon_entropy(); // Collect results and statistics diff --git a/tests/regression_tests/random_ray_entropy/__init__.py b/tests/regression_tests/random_ray_entropy/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/regression_tests/random_ray_entropy/geometry.xml b/tests/regression_tests/random_ray_entropy/geometry.xml new file mode 100644 index 00000000000..4c87bbbfb9a --- /dev/null +++ b/tests/regression_tests/random_ray_entropy/geometry.xml @@ -0,0 +1,88 @@ + + + + + + 12.5 12.5 12.5 + 8 8 8 + 0.0 0.0 0.0 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 +1 1 1 1 1 1 1 1 + + + + + + + + diff --git a/tests/regression_tests/random_ray_entropy/materials.xml b/tests/regression_tests/random_ray_entropy/materials.xml new file mode 100644 index 00000000000..5a6f93414bb --- /dev/null +++ b/tests/regression_tests/random_ray_entropy/materials.xml @@ -0,0 +1,8 @@ + + + mgxs.h5 + + + + + diff --git a/tests/regression_tests/random_ray_entropy/mgxs.h5 b/tests/regression_tests/random_ray_entropy/mgxs.h5 new file mode 100644 index 0000000000000000000000000000000000000000..6ce80bf713a8d5ff29700ba59e982e18f99b5403 GIT binary patch literal 10664 zcmeHN%}*0S6o1<)ELx=~2P1yeL;JB5M`%OA4UJMuu{yU;m}}jFYub= zpCp>Wc%w?`qzL4JLLk-KJs<`=jH9M_TERFYFm72kyJxt}HjSLnQCudeLWQygKO6SV(mu^{#vDtpJMgnd zH{3=&5sl;2%Eu!cjybM9GwIIQ3|eA|^>K9`h0dQi?=_$Ct!2L!-+%vhQ~3XQ!s+(o zk0k{bjN?Gc@yAL;^%%{l`++9`bj_V4+@MK6%Q@D1c^N!HbJV{c83gv_Q{XH7@ zLUFe!NP%DEcLnpS4N4!}|Be9huotfg$Yp`!8G*|jVO6cwN1#3`^AJf<+$ z;db}k2Yj;uLxT^6kOlNSNdC@?g5Pacu$ja1uHg#02Ep%5%2c{A9m}hQ&q)QJ zb5gOo1FX=yIu|vppSS1FZtb80ix}W%XQ$2Y2?A0_%E1fc90x*l}8~J3RX;`i{jvLfPglKxS;(OKWW1?go4)haasERZ?)r} zg}UG$wGRwK45412!0~}z?V16K?LHMyO*|C8v~|7xQd)UjRl3eE`ovRdPeNFIJeKMT Fk6-_XIk5l$ literal 0 HcmV?d00001 diff --git a/tests/regression_tests/random_ray_entropy/results_true.dat b/tests/regression_tests/random_ray_entropy/results_true.dat new file mode 100644 index 00000000000..25425453871 --- /dev/null +++ b/tests/regression_tests/random_ray_entropy/results_true.dat @@ -0,0 +1,13 @@ +k-combined: +1.000000E+00 0.000000E+00 +entropy: +8.863421E+00 +8.933584E+00 +8.960553E+00 +8.967921E+00 +8.976016E+00 +8.981856E+00 +8.983670E+00 +8.986584E+00 +8.987732E+00 +8.988186E+00 diff --git a/tests/regression_tests/random_ray_entropy/settings.xml b/tests/regression_tests/random_ray_entropy/settings.xml new file mode 100644 index 00000000000..81deaa7751d --- /dev/null +++ b/tests/regression_tests/random_ray_entropy/settings.xml @@ -0,0 +1,17 @@ + + + eigenvalue + 100 + 10 + 5 + multi-group + + + + 0.0 0.0 0.0 100.0 100.0 100.0 + + + 40.0 + 400.0 + + diff --git a/tests/regression_tests/random_ray_entropy/test.py b/tests/regression_tests/random_ray_entropy/test.py new file mode 100644 index 00000000000..a3cba65ad0b --- /dev/null +++ b/tests/regression_tests/random_ray_entropy/test.py @@ -0,0 +1,33 @@ +import glob +import os + +from openmc import StatePoint + +from tests.testing_harness import TestHarness + + +class EntropyTestHarness(TestHarness): + def _get_results(self): + """Digest info in the statepoint and return as a string.""" + # Read the statepoint file. + statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] + with StatePoint(statepoint) as sp: + # Write out k-combined. + outstr = 'k-combined:\n' + outstr += '{:12.6E} {:12.6E}\n'.format(sp.keff.n, sp.keff.s) + + # Write out entropy data. + outstr += 'entropy:\n' + results = ['{:12.6E}'.format(x) for x in sp.entropy] + outstr += '\n'.join(results) + '\n' + + return outstr + +''' +# This test is adapted from "Monte Carlo power iteration: Entropy and spatial correlations," +M. Nowak et al. The cross sections are defined explicitly so that the value for entropy +is exactly 9 and the eigenvalue is exactly 1. +''' +def test_entropy(): + harness = EntropyTestHarness('statepoint.10.h5') + harness.main() From ac0ad0bac2aaae0b71f625248b56933bc1138699 Mon Sep 17 00:00:00 2001 From: Olek <45364492+yardasol@users.noreply.github.com> Date: Fri, 28 Jun 2024 10:18:17 -0400 Subject: [PATCH 2/3] Fix hyperlinks in `random_ray.rst` (#3064) --- docs/source/methods/random_ray.rst | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/source/methods/random_ray.rst b/docs/source/methods/random_ray.rst index d46d3ad4165..7a29a187516 100644 --- a/docs/source/methods/random_ray.rst +++ b/docs/source/methods/random_ray.rst @@ -10,7 +10,7 @@ Random Ray What is Random Ray? ------------------- -`Random ray `_ is a stochastic transport method, closely related to +`Random ray `_ is a stochastic transport method, closely related to the deterministic Method of Characteristics (MOC) [Askew-1972]_. Rather than each ray representing a single neutron as in Monte Carlo, it represents a characteristic line through the simulation geometry upon which the transport @@ -82,7 +82,7 @@ Random Ray Numerical Derivation In this section, we will derive the numerical basis for the random ray solver mode in OpenMC. The derivation of random ray is also discussed in several papers -(`1 `_, `2 `_, `3 `_), and some of those +(`1 `_, `2 `_, `3 `_), and some of those derivations are reproduced here verbatim. Several extensions are also made to add clarity, particularly on the topic of OpenMC's treatment of cell volumes in the random ray solver. @@ -428,7 +428,7 @@ of terms. Mathematically, such cancellation allows us to arrive at the following This derivation appears mathematically sound at first glance but unfortunately raises a serious issue as discussed in more depth by `Tramm et al. -`_ and `Cosgrove and Tramm `_. Namely, the second +`_ and `Cosgrove and Tramm `_. Namely, the second term: .. math:: @@ -607,7 +607,7 @@ guess can be made by taking the isotropic source from the FSR the ray was sampled in, direct usage of this quantity would result in significant bias and error being imparted on the simulation. -Thus, an `on-the-fly approximation method `_ was developed (known +Thus, an `on-the-fly approximation method `_ was developed (known as the "dead zone"), where the first several mean free paths of a ray are considered to be "inactive" or "read only". In this sense, the angular flux is solved for using the MOC equation, but the ray does not "tally" any scalar flux From 391450ce01c4222c4a24466d749ec1dc5ac61b19 Mon Sep 17 00:00:00 2001 From: John Tramm Date: Fri, 28 Jun 2024 11:41:20 -0500 Subject: [PATCH 3/3] Random Ray Normalization Improvements (#3051) Co-authored-by: Olek <45364492+yardasol@users.noreply.github.com> --- docs/source/methods/random_ray.rst | 14 + docs/source/usersguide/random_ray.rst | 21 + .../openmc/random_ray/flat_source_domain.h | 5 + openmc/settings.py | 12 + src/random_ray/flat_source_domain.cpp | 125 +- src/settings.cpp | 4 + .../random_ray_basic/inputs_true.dat | 1 + .../regression_tests/random_ray_basic/test.py | 1 + .../False_hybrid/inputs_true.dat | 1018 +++++++++++++++++ .../False_hybrid/results_true.dat | 9 + .../True_hybrid/inputs_true.dat | 1018 +++++++++++++++++ .../True_hybrid/results_true.dat | 9 + .../random_ray_cube/__init__.py | 0 .../regression_tests/random_ray_cube/test.py | 231 ++++ .../cell/inputs_true.dat | 1 + .../cell/results_true.dat | 86 +- .../material/inputs_true.dat | 1 + .../material/results_true.dat | 84 +- .../random_ray_fixed_source/test.py | 1 + .../universe/inputs_true.dat | 1 + .../universe/results_true.dat | 84 +- .../random_ray_vacuum/inputs_true.dat | 1 + .../random_ray_vacuum/test.py | 1 + 23 files changed, 2573 insertions(+), 155 deletions(-) create mode 100644 tests/regression_tests/random_ray_cube/False_hybrid/inputs_true.dat create mode 100644 tests/regression_tests/random_ray_cube/False_hybrid/results_true.dat create mode 100644 tests/regression_tests/random_ray_cube/True_hybrid/inputs_true.dat create mode 100644 tests/regression_tests/random_ray_cube/True_hybrid/results_true.dat create mode 100644 tests/regression_tests/random_ray_cube/__init__.py create mode 100644 tests/regression_tests/random_ray_cube/test.py diff --git a/docs/source/methods/random_ray.rst b/docs/source/methods/random_ray.rst index 7a29a187516..45af2b0c894 100644 --- a/docs/source/methods/random_ray.rst +++ b/docs/source/methods/random_ray.rst @@ -740,6 +740,8 @@ scalar flux value for the FSR). global::volume[fsr] += s; } +.. _methods_random_tallies: + ------------------------ How are Tallies Handled? ------------------------ @@ -757,6 +759,18 @@ behavior if a single simulation cell is able to score to multiple filter mesh cells. In the future, the capability to fully support mesh tallies may be added to OpenMC, but for now this restriction needs to be respected. +Flux tallies are handled slightly differently than in Monte Carlo. By default, +in MC, flux tallies are reported in units of tracklength (cm), so must be +manually normalized by volume by the user to produce an estimate of flux in +units of cm\ :sup:`-2`\. Alternatively, MC flux tallies can be normalized via a +separated volume calculation process as discussed in the :ref:`Volume +Calculation Section`. In random ray, as the volumes are +computed on-the-fly as part of the transport process, the flux tallies can +easily be reported either in units of flux (cm\ :sup:`-2`\) or tracklength (cm). +By default, the unnormalized flux values (units of cm) will be reported. If the +user wishes to received volume normalized flux tallies, then an option for this +is available, as described in the :ref:`User Guide`. + .. _methods-shannon-entropy-random-ray: ----------------------------- diff --git a/docs/source/usersguide/random_ray.rst b/docs/source/usersguide/random_ray.rst index 2a038b12257..6df132859c7 100644 --- a/docs/source/usersguide/random_ray.rst +++ b/docs/source/usersguide/random_ray.rst @@ -330,6 +330,8 @@ of a two-dimensional 2x2 reflective pincell lattice: In the future, automated subdivision of FSRs via mesh overlay may be supported. +.. _usersguide_flux_norm: + ------- Tallies ------- @@ -367,6 +369,25 @@ Note that there is no difference between the analog, tracklength, and collision estimators in random ray mode as individual particles are not being simulated. Tracklength-style tally estimation is inherent to the random ray method. +As discussed in the random ray theory section on :ref:`Random Ray +Tallies`, by default flux tallies in the random ray mode +are not normalized by the spatial tally volumes such that flux tallies are in +units of cm. While the volume information is readily available as a byproduct of +random ray integration, the flux value is reported in unnormalized units of cm +so that the user will be able to compare "apples to apples" with the default +flux tallies from the Monte Carlo solver (also reported by default in units of +cm). If volume normalized flux tallies (in units of cm\ :sup:`-2`) are desired, +then the user can set the ``volume_normalized_flux_tallies`` field in the +:attr:`openmc.Settings.random_ray` dictionary to ``True``. An example is given +below: + +:: + + settings.random_ray['volume_normalized_flux_tallies'] = True + +Note that MC mode flux tallies can also be normalized by volume, as discussed in +the :ref:`Volume Calculation Section` of the user guide. + -------- Plotting -------- diff --git a/include/openmc/random_ray/flat_source_domain.h b/include/openmc/random_ray/flat_source_domain.h index badbb25fc2c..51938404037 100644 --- a/include/openmc/random_ray/flat_source_domain.h +++ b/include/openmc/random_ray/flat_source_domain.h @@ -108,6 +108,11 @@ class FlatSourceDomain { void all_reduce_replicated_source_regions(); void convert_external_sources(); void count_external_source_regions(); + double compute_fixed_source_normalization_factor() const; + + //---------------------------------------------------------------------------- + // Static Data members + static bool volume_normalized_flux_tallies_; //---------------------------------------------------------------------------- // Public Data members diff --git a/openmc/settings.py b/openmc/settings.py index fae6f638364..b048c3a8b34 100644 --- a/openmc/settings.py +++ b/openmc/settings.py @@ -157,6 +157,12 @@ class Settings: :ray_source: Starting ray distribution (must be uniform in space and angle) as specified by a :class:`openmc.SourceBase` object. + :volume_normalized_flux_tallies: + Whether to normalize flux tallies by volume (bool). The default + is 'False'. When enabled, flux tallies will be reported in units of + cm/cm^3. When disabled, flux tallies will be reported in units + of cm (i.e., total distance traveled by neutrons in the spatial + tally region). .. versionadded:: 0.15.0 resonance_scattering : dict @@ -1084,6 +1090,8 @@ def random_ray(self, random_ray: dict): random_ray[key], 0.0, True) elif key == 'ray_source': cv.check_type('random ray source', random_ray[key], SourceBase) + elif key == 'volume_normalized_flux_tallies': + cv.check_type('volume normalized flux tallies', random_ray[key], bool) else: raise ValueError(f'Unable to set random ray to "{key}" which is ' 'unsupported by OpenMC') @@ -1877,6 +1885,10 @@ def _random_ray_from_xml_element(self, root): elif child.tag == 'source': source = SourceBase.from_xml_element(child) self.random_ray['ray_source'] = source + elif child.tag == 'volume_normalized_flux_tallies': + self.random_ray['volume_normalized_flux_tallies'] = ( + child.text in ('true', '1') + ) def to_xml_element(self, mesh_memo=None): """Create a 'settings' element to be written to an XML file. diff --git a/src/random_ray/flat_source_domain.cpp b/src/random_ray/flat_source_domain.cpp index 792e97da0c1..29b72c77bed 100644 --- a/src/random_ray/flat_source_domain.cpp +++ b/src/random_ray/flat_source_domain.cpp @@ -23,6 +23,9 @@ namespace openmc { // FlatSourceDomain implementation //============================================================================== +// Static Variable Declarations +bool FlatSourceDomain::volume_normalized_flux_tallies_ {false}; + FlatSourceDomain::FlatSourceDomain() : negroups_(data::mg.num_energy_groups_) { // Count the number of source regions, compute the cell offset @@ -81,15 +84,17 @@ FlatSourceDomain::FlatSourceDomain() : negroups_(data::mg.num_energy_groups_) } // Initialize tally volumes - tally_volumes_.resize(model::tallies.size()); - for (int i = 0; i < model::tallies.size(); i++) { - // Get the shape of the 3D result tensor - auto shape = model::tallies[i]->results().shape(); - - // Create a new 2D tensor with the same size as the first - // two dimensions of the 3D tensor - tally_volumes_[i] = - xt::xtensor::from_shape({shape[0], shape[1]}); + if (volume_normalized_flux_tallies_) { + tally_volumes_.resize(model::tallies.size()); + for (int i = 0; i < model::tallies.size(); i++) { + // Get the shape of the 3D result tensor + auto shape = model::tallies[i]->results().shape(); + + // Create a new 2D tensor with the same size as the first + // two dimensions of the 3D tensor + tally_volumes_[i] = + xt::xtensor::from_shape({shape[0], shape[1]}); + } } // Compute simulation domain volume based on ray source @@ -462,11 +467,63 @@ void FlatSourceDomain::convert_source_regions_to_tallies() // Set the volume accumulators to zero for all tallies void FlatSourceDomain::reset_tally_volumes() { + if (volume_normalized_flux_tallies_) { #pragma omp parallel for - for (int i = 0; i < tally_volumes_.size(); i++) { - auto& tensor = tally_volumes_[i]; - tensor.fill(0.0); // Set all elements of the tensor to 0.0 + for (int i = 0; i < tally_volumes_.size(); i++) { + auto& tensor = tally_volumes_[i]; + tensor.fill(0.0); // Set all elements of the tensor to 0.0 + } + } +} + +// In fixed source mode, due to the way that volumetric fixed sources are +// converted and applied as volumetric sources in one or more source regions, +// we need to perform an additional normalization step to ensure that the +// reported scalar fluxes are in units per source neutron. This allows for +// direct comparison of reported tallies to Monte Carlo flux results. +// This factor needs to be computed at each iteration, as it is based on the +// volume estimate of each FSR, which improves over the course of the simulation +double FlatSourceDomain::compute_fixed_source_normalization_factor() const +{ + // If we are not in fixed source mode, then there are no external sources + // so no normalization is needed. + if (settings::run_mode != RunMode::FIXED_SOURCE) { + return 1.0; + } + + // Step 1 is to sum over all source regions and energy groups to get the + // total external source strength in the simulation. + double simulation_external_source_strength = 0.0; +#pragma omp parallel for reduction(+ : simulation_external_source_strength) + for (int sr = 0; sr < n_source_regions_; sr++) { + int material = material_[sr]; + double volume = volume_[sr] * simulation_volume_; + for (int e = 0; e < negroups_; e++) { + // Temperature and angle indices, if using multiple temperature + // data sets and/or anisotropic data sets. + // TODO: Currently assumes we are only using single temp/single + // angle data. + const int t = 0; + const int a = 0; + float sigma_t = data::mg.macro_xs_[material].get_xs( + MgxsType::TOTAL, e, nullptr, nullptr, nullptr, t, a); + simulation_external_source_strength += + external_source_[sr * negroups_ + e] * sigma_t * volume; + } + } + + // Step 2 is to determine the total user-specified external source strength + double user_external_source_strength = 0.0; + for (auto& ext_source : model::external_sources) { + user_external_source_strength += ext_source->strength(); } + + // The correction factor is the ratio of the user-specified external source + // strength to the simulation external source strength. + double source_normalization_factor = + user_external_source_strength / simulation_external_source_strength; + + return source_normalization_factor; } // Tallying in random ray is not done directly during transport, rather, @@ -492,6 +549,9 @@ void FlatSourceDomain::random_ray_tally() const int t = 0; const int a = 0; + double source_normalization_factor = + compute_fixed_source_normalization_factor(); + // We loop over all source regions and energy groups. For each // element, we check if there are any scores needed and apply // them. @@ -510,7 +570,7 @@ void FlatSourceDomain::random_ray_tally() double material = material_[sr]; for (int g = 0; g < negroups_; g++) { int idx = sr * negroups_ + g; - double flux = scalar_flux_new_[idx]; + double flux = scalar_flux_new_[idx] * source_normalization_factor; // Determine numerical score value for (auto& task : tally_task_[idx]) { @@ -561,11 +621,13 @@ void FlatSourceDomain::random_ray_tally() // For flux tallies, the total volume of the spatial region is needed // for normalizing the flux. We store this volume in a separate tensor. // We only contribute to each volume tally bin once per FSR. - for (const auto& task : volume_task_[sr]) { - if (task.score_type == SCORE_FLUX) { + if (volume_normalized_flux_tallies_) { + for (const auto& task : volume_task_[sr]) { + if (task.score_type == SCORE_FLUX) { #pragma omp atomic - tally_volumes_[task.tally_idx](task.filter_idx, task.score_idx) += - volume; + tally_volumes_[task.tally_idx](task.filter_idx, task.score_idx) += + volume; + } } } } // end FSR loop @@ -575,16 +637,18 @@ void FlatSourceDomain::random_ray_tally() // and then scores. For each score, we check the tally data structure to // see what index that score corresponds to. If that score is a flux score, // then we divide it by volume. - for (int i = 0; i < model::tallies.size(); i++) { - Tally& tally {*model::tallies[i]}; + if (volume_normalized_flux_tallies_) { + for (int i = 0; i < model::tallies.size(); i++) { + Tally& tally {*model::tallies[i]}; #pragma omp parallel for - for (int bin = 0; bin < tally.n_filter_bins(); bin++) { - for (int score_idx = 0; score_idx < tally.n_scores(); score_idx++) { - auto score_type = tally.scores_[score_idx]; - if (score_type == SCORE_FLUX) { - double vol = tally_volumes_[i](bin, score_idx); - if (vol > 0.0) { - tally.results_(bin, score_idx, TallyResult::VALUE) /= vol; + for (int bin = 0; bin < tally.n_filter_bins(); bin++) { + for (int score_idx = 0; score_idx < tally.n_scores(); score_idx++) { + auto score_type = tally.scores_[score_idx]; + if (score_type == SCORE_FLUX) { + double vol = tally_volumes_[i](bin, score_idx); + if (vol > 0.0) { + tally.results_(bin, score_idx, TallyResult::VALUE) /= vol; + } } } } @@ -767,6 +831,9 @@ void FlatSourceDomain::output_to_vtk() const } } + double source_normalization_factor = + compute_fixed_source_normalization_factor(); + // Open file for writing std::FILE* plot = std::fopen(filename.c_str(), "wb"); @@ -786,7 +853,8 @@ void FlatSourceDomain::output_to_vtk() const std::fprintf(plot, "LOOKUP_TABLE default\n"); for (int fsr : voxel_indices) { int64_t source_element = fsr * negroups_ + g; - float flux = scalar_flux_final_[source_element]; + float flux = + scalar_flux_final_[source_element] * source_normalization_factor; flux /= (settings::n_batches - settings::n_inactive); flux = convert_to_big_endian(flux); std::fwrite(&flux, sizeof(float), 1, plot); @@ -819,7 +887,8 @@ void FlatSourceDomain::output_to_vtk() const int mat = material_[fsr]; for (int g = 0; g < negroups_; g++) { int64_t source_element = fsr * negroups_ + g; - float flux = scalar_flux_final_[source_element]; + float flux = + scalar_flux_final_[source_element] * source_normalization_factor; flux /= (settings::n_batches - settings::n_inactive); float Sigma_f = data::mg.macro_xs_[mat].get_xs( MgxsType::FISSION, g, nullptr, nullptr, nullptr, 0, 0); diff --git a/src/settings.cpp b/src/settings.cpp index 4ffa50cdf45..b92b77df937 100644 --- a/src/settings.cpp +++ b/src/settings.cpp @@ -269,6 +269,10 @@ void get_run_parameters(pugi::xml_node node_base) } else { fatal_error("Specify random ray source in settings XML"); } + if (check_for_node(random_ray_node, "volume_normalized_flux_tallies")) { + FlatSourceDomain::volume_normalized_flux_tallies_ = + get_node_value_bool(random_ray_node, "volume_normalized_flux_tallies"); + } } } diff --git a/tests/regression_tests/random_ray_basic/inputs_true.dat b/tests/regression_tests/random_ray_basic/inputs_true.dat index 97b7906f7b2..a2b058f2bdb 100644 --- a/tests/regression_tests/random_ray_basic/inputs_true.dat +++ b/tests/regression_tests/random_ray_basic/inputs_true.dat @@ -85,6 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 + True diff --git a/tests/regression_tests/random_ray_basic/test.py b/tests/regression_tests/random_ray_basic/test.py index 1727a63716c..c00d25880c5 100644 --- a/tests/regression_tests/random_ray_basic/test.py +++ b/tests/regression_tests/random_ray_basic/test.py @@ -190,6 +190,7 @@ def random_ray_model() -> openmc.Model: settings.random_ray['distance_active'] = 100.0 settings.random_ray['distance_inactive'] = 20.0 settings.random_ray['ray_source'] = rr_source + settings.random_ray['volume_normalized_flux_tallies'] = True ############################################################################### # Define tallies diff --git a/tests/regression_tests/random_ray_cube/False_hybrid/inputs_true.dat b/tests/regression_tests/random_ray_cube/False_hybrid/inputs_true.dat new file mode 100644 index 00000000000..82c24291b30 --- /dev/null +++ b/tests/regression_tests/random_ray_cube/False_hybrid/inputs_true.dat @@ -0,0 +1,1018 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + 1.0 1.0 1.0 + 30 30 30 + 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3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 + +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 + +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 + + + + + + + + + + fixed source + 90 + 10 + 5 + + + 100.0 1.0 + + + universe + 1 + + + multi-group + + 500.0 + 100.0 + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + True + + + + + 1 + + + 2 + + + 3 + + + 3 + flux + tracklength + + + 2 + flux + tracklength + + + 1 + flux + tracklength + + + diff --git a/tests/regression_tests/random_ray_cube/True_hybrid/results_true.dat b/tests/regression_tests/random_ray_cube/True_hybrid/results_true.dat new file mode 100644 index 00000000000..4a29967407d --- /dev/null +++ b/tests/regression_tests/random_ray_cube/True_hybrid/results_true.dat @@ -0,0 +1,9 @@ +tally 1: +-5.230164E+02 +1.818988E+05 +tally 2: +3.067508E-02 +2.037701E-04 +tally 3: +1.941220E-03 +7.892297E-07 diff --git a/tests/regression_tests/random_ray_cube/__init__.py b/tests/regression_tests/random_ray_cube/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/regression_tests/random_ray_cube/test.py b/tests/regression_tests/random_ray_cube/test.py new file mode 100644 index 00000000000..51d61ae797c --- /dev/null +++ b/tests/regression_tests/random_ray_cube/test.py @@ -0,0 +1,231 @@ +import os + +import numpy as np +import openmc +from openmc.utility_funcs import change_directory +import pytest + +from tests.testing_harness import TolerantPyAPITestHarness + +# Creates a 3 region cube with different fills in each region +def fill_cube(N, n_1, n_2, fill_1, fill_2, fill_3): + cube = [[[0 for _ in range(N)] for _ in range(N)] for _ in range(N)] + for i in range(N): + for j in range(N): + for k in range(N): + if i < n_1 and j >= (N-n_1) and k < n_1: + cube[i][j][k] = fill_1 + elif i < n_2 and j >= (N-n_2) and k < n_2: + cube[i][j][k] = fill_2 + else: + cube[i][j][k] = fill_3 + return cube + +class MGXSTestHarness(TolerantPyAPITestHarness): + def _cleanup(self): + super()._cleanup() + f = 'mgxs.h5' + if os.path.exists(f): + os.remove(f) + +def create_random_ray_model(volume_normalize, estimator): + openmc.reset_auto_ids() + ############################################################################### + # Create multigroup data + + # Instantiate the energy group data + ebins = [1e-5, 20.0e6] + groups = openmc.mgxs.EnergyGroups(group_edges=ebins) + + void_sigma_a = 4.0e-6 + void_sigma_s = 3.0e-4 + void_mat_data = openmc.XSdata('void', groups) + void_mat_data.order = 0 + void_mat_data.set_total([void_sigma_a + void_sigma_s]) + void_mat_data.set_absorption([void_sigma_a]) + void_mat_data.set_scatter_matrix(np.rollaxis(np.array([[[void_sigma_s]]]),0,3)) + + absorber_sigma_a = 0.75 + absorber_sigma_s = 0.25 + absorber_mat_data = openmc.XSdata('absorber', groups) + absorber_mat_data.order = 0 + absorber_mat_data.set_total([absorber_sigma_a + absorber_sigma_s]) + absorber_mat_data.set_absorption([absorber_sigma_a]) + absorber_mat_data.set_scatter_matrix(np.rollaxis(np.array([[[absorber_sigma_s]]]),0,3)) + + multiplier = 0.1 + source_sigma_a = void_sigma_a * multiplier + source_sigma_s = void_sigma_s * multiplier + source_mat_data = openmc.XSdata('source', groups) + source_mat_data.order = 0 + print(source_sigma_a + source_sigma_s) + source_mat_data.set_total([source_sigma_a + source_sigma_s]) + source_mat_data.set_absorption([source_sigma_a]) + source_mat_data.set_scatter_matrix(np.rollaxis(np.array([[[source_sigma_s]]]),0,3)) + + mg_cross_sections_file = openmc.MGXSLibrary(groups) + mg_cross_sections_file.add_xsdatas([source_mat_data, void_mat_data, absorber_mat_data]) + mg_cross_sections_file.export_to_hdf5() + + ############################################################################### + # Create materials for the problem + + # Instantiate some Macroscopic Data + source_data = openmc.Macroscopic('source') + void_data = openmc.Macroscopic('void') + absorber_data = openmc.Macroscopic('absorber') + + # Instantiate some Materials and register the appropriate Macroscopic objects + source_mat = openmc.Material(name='source') + source_mat.set_density('macro', 1.0) + source_mat.add_macroscopic(source_data) + + void_mat = openmc.Material(name='void') + void_mat.set_density('macro', 1.0) + void_mat.add_macroscopic(void_data) + + absorber_mat = openmc.Material(name='absorber') + absorber_mat.set_density('macro', 1.0) + absorber_mat.add_macroscopic(absorber_data) + + # Instantiate a Materials collection and export to XML + materials_file = openmc.Materials([source_mat, void_mat, absorber_mat]) + materials_file.cross_sections = "mgxs.h5" + + ############################################################################### + # Define problem geometry + + source_cell = openmc.Cell(fill=source_mat, name='infinite source region') + void_cell = openmc.Cell(fill=void_mat, name='infinite void region') + absorber_cell = openmc.Cell(fill=absorber_mat, name='infinite absorber region') + + source_universe = openmc.Universe() + source_universe.add_cells([source_cell]) + + void_universe = openmc.Universe() + void_universe.add_cells([void_cell]) + + absorber_universe = openmc.Universe() + absorber_universe.add_cells([absorber_cell]) + + absorber_width = 30.0 + n_base = 6 + + # This variable can be increased above 1 to refine the FSR mesh resolution further + refinement_level = 5 + + n = n_base * refinement_level + pitch = absorber_width / n + + pattern = fill_cube(n, 1*refinement_level, 5*refinement_level, source_universe, void_universe, absorber_universe) + + lattice = openmc.RectLattice() + lattice.lower_left = [0.0, 0.0, 0.0] + lattice.pitch = [pitch, pitch, pitch] + lattice.universes = pattern + #print(lattice) + + lattice_cell = openmc.Cell(fill=lattice) + + lattice_uni = openmc.Universe() + lattice_uni.add_cells([lattice_cell]) + + x_low = openmc.XPlane(x0=0.0,boundary_type='reflective') + x_high = openmc.XPlane(x0=absorber_width,boundary_type='vacuum') + + y_low = openmc.YPlane(y0=0.0,boundary_type='reflective') + y_high = openmc.YPlane(y0=absorber_width,boundary_type='vacuum') + + z_low = openmc.ZPlane(z0=0.0,boundary_type='reflective') + z_high = openmc.ZPlane(z0=absorber_width,boundary_type='vacuum') + + full_domain = openmc.Cell(fill=lattice_uni, region=+x_low & -x_high & +y_low & -y_high & +z_low & -z_high, name='full domain') + + root = openmc.Universe(name='root universe') + root.add_cell(full_domain) + + # Create a geometry with the two cells and export to XML + geometry = openmc.Geometry(root) + + ############################################################################### + # Define problem settings + + # Instantiate a Settings object, set all runtime parameters, and export to XML + settings = openmc.Settings() + settings.energy_mode = "multi-group" + settings.inactive = 5 + settings.batches = 10 + settings.particles = 90 + settings.run_mode = 'fixed source' + + # Create an initial uniform spatial source for ray integration + lower_left_ray = [0.0, 0.0, 0.0] + upper_right_ray = [absorber_width, absorber_width, absorber_width] + uniform_dist_ray = openmc.stats.Box(lower_left_ray, upper_right_ray, only_fissionable=False) + rr_source = openmc.IndependentSource(space=uniform_dist_ray) + + settings.random_ray['distance_active'] = 500.0 + settings.random_ray['distance_inactive'] = 100.0 + settings.random_ray['ray_source'] = rr_source + settings.random_ray['volume_normalized_flux_tallies'] = volume_normalize + + #settings.random_ray['volume_estimator'] = estimator + + # Create the neutron source in the bottom right of the moderator + strengths = [1.0] # Good - fast group appears largest (besides most thermal) + midpoints = [100.0] + energy_distribution = openmc.stats.Discrete(x=midpoints,p=strengths) + + source = openmc.IndependentSource(energy=energy_distribution, constraints={'domains':[source_universe]}, strength=3.14) + + settings.source = [source] + + ############################################################################### + # Define tallies + + estimator = 'tracklength' + + absorber_filter = openmc.MaterialFilter(absorber_mat) + absorber_tally = openmc.Tally(name="Absorber Tally") + absorber_tally.filters = [absorber_filter] + absorber_tally.scores = ['flux'] + absorber_tally.estimator = estimator + + void_filter = openmc.MaterialFilter(void_mat) + void_tally = openmc.Tally(name="Void Tally") + void_tally.filters = [void_filter] + void_tally.scores = ['flux'] + void_tally.estimator = estimator + + source_filter = openmc.MaterialFilter(source_mat) + source_tally = openmc.Tally(name="Source Tally") + source_tally.filters = [source_filter] + source_tally.scores = ['flux'] + source_tally.estimator = estimator + + # Instantiate a Tallies collection and export to XML + tallies = openmc.Tallies([source_tally, void_tally, absorber_tally]) + + ############################################################################### + # Assmble Model + + model = openmc.model.Model() + model.geometry = geometry + model.materials = materials_file + model.settings = settings + model.xs_data = mg_cross_sections_file + model.tallies = tallies + + return model + +@pytest.mark.parametrize("volume_normalize, estimator", [ + (False, "hybrid"), + (True, "hybrid") +]) +def test_random_ray_cube(volume_normalize, estimator): + # Generating a unique directory name from the parameters + directory_name = f"{volume_normalize}_{estimator}" + with change_directory(directory_name): + model = create_random_ray_model(volume_normalize, estimator) + harness = MGXSTestHarness('statepoint.10.h5', model) + harness.main() \ No newline at end of file diff --git a/tests/regression_tests/random_ray_fixed_source/cell/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source/cell/inputs_true.dat index 99e67745a26..a8eaa009661 100644 --- a/tests/regression_tests/random_ray_fixed_source/cell/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/cell/inputs_true.dat @@ -153,6 +153,7 @@ 400.0 100.0 + False 0.0 0.0 0.0 60.0 100.0 60.0 diff --git a/tests/regression_tests/random_ray_fixed_source/cell/results_true.dat b/tests/regression_tests/random_ray_fixed_source/cell/results_true.dat index df923ab236a..ba1254d384d 100644 --- a/tests/regression_tests/random_ray_fixed_source/cell/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/cell/results_true.dat @@ -1,47 +1,47 @@ tally 1: -3.751048E+01 +3.751047E+01 2.841797E+02 -9.930788E+00 -1.988180E+01 -3.781121E+00 -3.005165E+00 -2.383139E+00 -1.232560E+00 -1.561884E+00 -6.440577E-01 -1.089787E+00 -3.724896E-01 -6.608456E-01 -1.285592E-01 -2.372611E-01 -1.601299E-02 -7.814803E-02 -1.765829E-03 -2.862108E-02 -2.460129E-04 +1.000671E+01 +2.020214E+01 +3.979569E+00 +3.330838E+00 +2.552971E+00 +1.407542E+00 +1.736764E+00 +7.948004E-01 +1.178834E+00 +4.328006E-01 +6.953895E-01 +1.408391E-01 +2.389347E-01 +1.617450E-02 +8.128516E-02 +1.903860E-03 +2.764062E-02 +2.285458E-04 tally 2: -1.089787E+00 -3.724896E-01 -3.767926E-01 -3.724399E-02 -8.614121E-02 -1.526889E-03 -3.610725E-02 -2.629885E-04 -1.466261E-02 -4.536997E-05 -4.653106E-03 -4.381672E-06 +1.178834E+00 +4.328006E-01 +3.982124E-01 +4.138078E-02 +9.676374E-02 +1.919297E-03 +3.944531E-02 +3.133733E-04 +1.554518E-02 +5.084822E-05 +4.815079E-03 +4.681450E-06 tally 3: -1.617918E-03 -6.317049E-07 -1.161473E-03 -2.789553E-07 -1.198879E-03 -3.189531E-07 -1.031737E-03 -2.207381E-07 -5.466329E-04 -6.166808E-08 -2.146062E-04 -9.937520E-09 +1.635823E-03 +6.482611E-07 +1.248235E-03 +3.227247E-07 +1.248195E-03 +3.488233E-07 +1.030935E-03 +2.206418E-07 +5.670315E-04 +6.648507E-08 +2.393638E-04 +1.242517E-08 diff --git a/tests/regression_tests/random_ray_fixed_source/material/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source/material/inputs_true.dat index 7fde0c419b5..e3ad3703b6e 100644 --- a/tests/regression_tests/random_ray_fixed_source/material/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/material/inputs_true.dat @@ -153,6 +153,7 @@ 400.0 100.0 + False 0.0 0.0 0.0 60.0 100.0 60.0 diff --git a/tests/regression_tests/random_ray_fixed_source/material/results_true.dat b/tests/regression_tests/random_ray_fixed_source/material/results_true.dat index e3d52890919..ba1254d384d 100644 --- a/tests/regression_tests/random_ray_fixed_source/material/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/material/results_true.dat @@ -1,47 +1,47 @@ tally 1: 3.751047E+01 2.841797E+02 -9.930788E+00 -1.988181E+01 -3.781121E+00 -3.005165E+00 -2.383139E+00 -1.232560E+00 -1.561884E+00 -6.440577E-01 -1.089787E+00 -3.724896E-01 -6.608456E-01 -1.285592E-01 -2.372611E-01 -1.601299E-02 -7.814803E-02 -1.765829E-03 -2.862108E-02 -2.460129E-04 +1.000671E+01 +2.020214E+01 +3.979569E+00 +3.330838E+00 +2.552971E+00 +1.407542E+00 +1.736764E+00 +7.948004E-01 +1.178834E+00 +4.328006E-01 +6.953895E-01 +1.408391E-01 +2.389347E-01 +1.617450E-02 +8.128516E-02 +1.903860E-03 +2.764062E-02 +2.285458E-04 tally 2: -1.089787E+00 -3.724896E-01 -3.767925E-01 -3.724398E-02 -8.614120E-02 -1.526889E-03 -3.610725E-02 -2.629885E-04 -1.466261E-02 -4.536997E-05 -4.653106E-03 -4.381672E-06 +1.178834E+00 +4.328006E-01 +3.982124E-01 +4.138078E-02 +9.676374E-02 +1.919297E-03 +3.944531E-02 +3.133733E-04 +1.554518E-02 +5.084822E-05 +4.815079E-03 +4.681450E-06 tally 3: -1.617918E-03 -6.317049E-07 -1.161473E-03 -2.789553E-07 -1.198879E-03 -3.189531E-07 -1.031737E-03 -2.207381E-07 -5.466329E-04 -6.166809E-08 -2.146062E-04 -9.937520E-09 +1.635823E-03 +6.482611E-07 +1.248235E-03 +3.227247E-07 +1.248195E-03 +3.488233E-07 +1.030935E-03 +2.206418E-07 +5.670315E-04 +6.648507E-08 +2.393638E-04 +1.242517E-08 diff --git a/tests/regression_tests/random_ray_fixed_source/test.py b/tests/regression_tests/random_ray_fixed_source/test.py index 41a6c35bb03..7ceadca5b93 100644 --- a/tests/regression_tests/random_ray_fixed_source/test.py +++ b/tests/regression_tests/random_ray_fixed_source/test.py @@ -251,6 +251,7 @@ def create_random_ray_model(domain_type): settings.random_ray['distance_active'] = 400.0 settings.random_ray['distance_inactive'] = 100.0 + settings.random_ray['volume_normalized_flux_tallies'] = False # Create an initial uniform spatial source for ray integration lower_left = (0.0, 0.0, 0.0) diff --git a/tests/regression_tests/random_ray_fixed_source/universe/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source/universe/inputs_true.dat index 349917fee72..efbc03adf8c 100644 --- a/tests/regression_tests/random_ray_fixed_source/universe/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/universe/inputs_true.dat @@ -153,6 +153,7 @@ 400.0 100.0 + False 0.0 0.0 0.0 60.0 100.0 60.0 diff --git a/tests/regression_tests/random_ray_fixed_source/universe/results_true.dat b/tests/regression_tests/random_ray_fixed_source/universe/results_true.dat index 36d24e939af..ba1254d384d 100644 --- a/tests/regression_tests/random_ray_fixed_source/universe/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source/universe/results_true.dat @@ -1,47 +1,47 @@ tally 1: 3.751047E+01 2.841797E+02 -9.930788E+00 -1.988180E+01 -3.781121E+00 -3.005165E+00 -2.383139E+00 -1.232560E+00 -1.561884E+00 -6.440577E-01 -1.089787E+00 -3.724896E-01 -6.608456E-01 -1.285592E-01 -2.372611E-01 -1.601299E-02 -7.814803E-02 -1.765829E-03 -2.862107E-02 -2.460129E-04 +1.000671E+01 +2.020214E+01 +3.979569E+00 +3.330838E+00 +2.552971E+00 +1.407542E+00 +1.736764E+00 +7.948004E-01 +1.178834E+00 +4.328006E-01 +6.953895E-01 +1.408391E-01 +2.389347E-01 +1.617450E-02 +8.128516E-02 +1.903860E-03 +2.764062E-02 +2.285458E-04 tally 2: -1.089787E+00 -3.724896E-01 -3.767926E-01 -3.724399E-02 -8.614120E-02 -1.526889E-03 -3.610725E-02 -2.629885E-04 -1.466261E-02 -4.536997E-05 -4.653106E-03 -4.381672E-06 +1.178834E+00 +4.328006E-01 +3.982124E-01 +4.138078E-02 +9.676374E-02 +1.919297E-03 +3.944531E-02 +3.133733E-04 +1.554518E-02 +5.084822E-05 +4.815079E-03 +4.681450E-06 tally 3: -1.617918E-03 -6.317049E-07 -1.161473E-03 -2.789553E-07 -1.198879E-03 -3.189531E-07 -1.031737E-03 -2.207381E-07 -5.466329E-04 -6.166808E-08 -2.146062E-04 -9.937520E-09 +1.635823E-03 +6.482611E-07 +1.248235E-03 +3.227247E-07 +1.248195E-03 +3.488233E-07 +1.030935E-03 +2.206418E-07 +5.670315E-04 +6.648507E-08 +2.393638E-04 +1.242517E-08 diff --git a/tests/regression_tests/random_ray_vacuum/inputs_true.dat b/tests/regression_tests/random_ray_vacuum/inputs_true.dat index 4ef10942005..5b2fa090596 100644 --- a/tests/regression_tests/random_ray_vacuum/inputs_true.dat +++ b/tests/regression_tests/random_ray_vacuum/inputs_true.dat @@ -85,6 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 + True diff --git a/tests/regression_tests/random_ray_vacuum/test.py b/tests/regression_tests/random_ray_vacuum/test.py index e9ca2252144..3923b8a815f 100644 --- a/tests/regression_tests/random_ray_vacuum/test.py +++ b/tests/regression_tests/random_ray_vacuum/test.py @@ -193,6 +193,7 @@ def random_ray_model() -> openmc.Model: settings.random_ray['distance_active'] = 100.0 settings.random_ray['distance_inactive'] = 20.0 settings.random_ray['ray_source'] = rr_source + settings.random_ray['volume_normalized_flux_tallies'] = True ############################################################################### # Define tallies