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Title: Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses

Abstract

Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses use high-fidelity transport codes to produce few-group parameters at the assembly level for use in low-order methods applied at the core level. Monte Carlo (MC) methods, which allow detailed and accurate modeling of the full geometry and energy details and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the several-decade-old methodology used in current practice. However, the prohibitive computational requirements associated with obtaining fully converged system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. A goal of current research at Oak Ridge National Laboratory (ORNL) is to change this paradigm by enabling the direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome is the slow non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, researchmore » has focused on development in the following two areas: (1) a hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The focus of this paper is limited to the first area mentioned above. It describes the FW-CADIS method applied to variance reduction of MC reactor analyses and provides initial results for calculating group-wise fluxes throughout a generic 2-D pressurized water reactor (PWR) quarter core model.« less

Authors:
 [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
992539
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: American Nuclear Society Winter Meeting, Las Vegas, NV, USA, 20101107, 20101111
Country of Publication:
United States
Language:
English
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; ALGORITHMS; CONVERGENCE; GEOMETRY; GOLD; IRRADIATION; ORNL; PHASE SPACE; PWR TYPE REACTORS; RADIATION TRANSPORT; SIMULATION; TEMPERATURE DISTRIBUTION; TRANSPORT; Hybrid Monte Carlo; FW-CADIS Method; Reactor Analysis

Citation Formats

Wagner, John C, and Mosher, Scott W. Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses. United States: N. p., 2010. Web.
Wagner, John C, & Mosher, Scott W. Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses. United States.
Wagner, John C, and Mosher, Scott W. Fri . "Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses". United States.
@article{osti_992539,
title = {Forward-Weighted CADIS Method for Variance Reduction of Monte Carlo Reactor Analyses},
author = {Wagner, John C and Mosher, Scott W},
abstractNote = {Current state-of-the-art tools and methods used to perform 'real' commercial reactor analyses use high-fidelity transport codes to produce few-group parameters at the assembly level for use in low-order methods applied at the core level. Monte Carlo (MC) methods, which allow detailed and accurate modeling of the full geometry and energy details and are considered the 'gold standard' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the several-decade-old methodology used in current practice. However, the prohibitive computational requirements associated with obtaining fully converged system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. A goal of current research at Oak Ridge National Laboratory (ORNL) is to change this paradigm by enabling the direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome is the slow non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, research has focused on development in the following two areas: (1) a hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The focus of this paper is limited to the first area mentioned above. It describes the FW-CADIS method applied to variance reduction of MC reactor analyses and provides initial results for calculating group-wise fluxes throughout a generic 2-D pressurized water reactor (PWR) quarter core model.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2010},
month = {1}
}

Conference:
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