Line data    Source code

       1             : /********************************************************************/
       2             : /*                  SOFTWARE COPYRIGHT NOTIFICATION                 */
       3             : /*                             Cardinal                             */
       4             : /*                                                                  */
       5             : /*                  (c) 2021 UChicago Argonne, LLC                  */
       6             : /*                        ALL RIGHTS RESERVED                       */
       7             : /*                                                                  */
       8             : /*                 Prepared by UChicago Argonne, LLC                */
       9             : /*               Under Contract No. DE-AC02-06CH11357               */
      10             : /*                With the U. S. Department of Energy               */
      11             : /*                                                                  */
      12             : /*             Prepared by Battelle Energy Alliance, LLC            */
      13             : /*               Under Contract No. DE-AC07-05ID14517               */
      14             : /*                With the U. S. Department of Energy               */
      15             : /*                                                                  */
      16             : /*                 See LICENSE for full restrictions                */
      17             : /********************************************************************/
      18             : 
      19             : #ifdef ENABLE_OPENMC_COUPLING
      20             : 
      21             : #include "LambdaEffective.h"
      22             : 
      23             : #include "OpenMCProblemBase.h"
      24             : 
      25             : #include "openmc/eigenvalue.h"
      26             : 
      27             : registerMooseObject("CardinalApp", LambdaEffective);
      28             : 
      29             : InputParameters
      30         105 : LambdaEffective::validParams()
      31             : {
      32         105 :   auto params = KEigenvalue::validParams();
      33         105 :   params.addClassDescription(
      34             :       "A post-processor which computes and returns the kinetics parameter $\\Lambda_{eff}$.");
      35         210 :   params.addParam<MooseEnum>(
      36             :       "output",
      37         210 :       getStatsOutputEnum(),
      38             :       "The value to output. Options are $\\Lambda_{eff}$ (mean), the standard deviation "
      39             :       "of $\\Lambda_{eff}$ (std_dev), or the relative error of $\\Lambda_{eff}$ (rel_err).");
      40             : 
      41         105 :   return params;
      42           0 : }
      43             : 
      44          29 : LambdaEffective::LambdaEffective(const InputParameters & parameters) : KEigenvalue(parameters)
      45             : {
      46          29 :   if (!_openmc_problem->computeKineticsParams())
      47           2 :     mooseError(
      48             :         "LambdaEffective can only be used if the OpenMC problem is computing kinetics parameters!");
      49          27 : }
      50             : 
      51             : Real
      52          30 : LambdaEffective::getValue() const
      53             : {
      54          30 :   const auto & ifp_tally = _openmc_problem->getCommonKineticsTally();
      55          30 :   const auto n = ifp_tally.n_realizations_;
      56             : 
      57          30 :   const auto num_sum = ifp_tally.results_.slice(
      58          30 :       openmc::tensor::all, 0, static_cast<int>(openmc::TallyResult::SUM))[0];
      59          30 :   const auto den_sum = ifp_tally.results_.slice(
      60          30 :       openmc::tensor::all, 1, static_cast<int>(openmc::TallyResult::SUM))[0];
      61             : 
      62          30 :   const auto num_ss = ifp_tally.results_.slice(
      63          30 :       openmc::tensor::all, 0, static_cast<int>(openmc::TallyResult::SUM_SQ))[0];
      64          30 :   const auto den_ss = ifp_tally.results_.slice(
      65          30 :       openmc::tensor::all, 1, static_cast<int>(openmc::TallyResult::SUM_SQ))[0];
      66             : 
      67          30 :   const auto mean_k = kMean(_type);
      68          30 :   const auto k_rel = kRelativeError();
      69             : 
      70          30 :   const Real lambda_eff = (num_sum / n) / (den_sum / n) / mean_k;
      71             : 
      72          30 :   const Real num_rel = _openmc_problem->relativeError(num_sum, num_ss, n);
      73          30 :   const Real den_rel = _openmc_problem->relativeError(den_sum, den_ss, n);
      74          30 :   const Real lambda_rel = std::sqrt(num_rel * num_rel + den_rel * den_rel + k_rel * k_rel);
      75             : 
      76          30 :   switch (_output)
      77             :   {
      78             :     case statistics::OutputEnum::Mean:
      79             :       return lambda_eff;
      80             : 
      81          10 :     case statistics::OutputEnum::StDev:
      82          10 :       return lambda_eff * lambda_rel;
      83             : 
      84          10 :     case statistics::OutputEnum::RelError:
      85          10 :       return lambda_rel;
      86             : 
      87           0 :     default:
      88           0 :       mooseError("Internal error: Unhandled statistics::OutputEnum enum in LambdaEffective.");
      89             :       break;
      90             :   }
      91             : 
      92             :   return lambda_eff;
      93             : }
      94             : 
      95             : #endif