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Title: WIELANDT ACCELERATION FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS

Authors:
 [1]
  1. Los Alamos National Laboratory
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1225276
Report Number(s):
LA-UR-07-1194
DOE Contract Number:
AC52-06NA25396
Resource Type:
Conference
Resource Relation:
Conference: ANS MATHEMATICS & COMPUTATION TOPICAL MEETING ; 200704 ; MONTEREY
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS

Citation Formats

BROWN, FORREST B. WIELANDT ACCELERATION FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS. United States: N. p., 2007. Web.
BROWN, FORREST B. WIELANDT ACCELERATION FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS. United States.
BROWN, FORREST B. Thu . "WIELANDT ACCELERATION FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS". United States. doi:. https://www.osti.gov/servlets/purl/1225276.
@article{osti_1225276,
title = {WIELANDT ACCELERATION FOR MCNP5 MONTE CARLO EIGENVALUE CALCULATIONS},
author = {BROWN, FORREST B.},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 22 00:00:00 EST 2007},
month = {Thu Feb 22 00:00:00 EST 2007}
}

Conference:
Other availability
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  • Monte Carlo eigenvalue calculations using a fixed number of histories per generation are biased. Previous work has shown that the bias in eigenvalue is generally smaller than observed standard deviations. In this paper, the authors propose a method for bounding [delta][psi] the bias in the unnormalized fission source. In addition, the authors construct a plausibility argument suggesting that the bias is generally insignificant. Results presented are for discretized diffusion calculations based on a Monte Carlo-generated source. Additional calculations have been run for true transport problems using a very fast, but more conventional, Monte Carlo code.
  • The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvectormore » of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.« less
  • Monte Carlo methods are used routinely to compute the eigenvalue and power distribution of reactor cores and fuel assemblies. Reproducibility of the results is vital to quality assurance for engineering design and to the process of developing and verifying a Monte Carlo code. In this paper, the authors outline methods used in the RACER Monte Carlo code, which ensure reproducibility, regardless of supergrouping or parallel processing, and which are completely consistent with conventional scalar Monte Carlo eigenvalue calculational methods.
  • It is well known that statistical estimates obtained from Monte Carlo criticality simulations can be adversely affected by cycle-to-cycle correlations in the fission source. In addition there are several other more fundamental issues that may lead to errors in Monte Carlo results. These factors can have a significant impact on the calculated eigenvalue, localized tally means and their associated standard deviations. In fact, modern Monte Carlo computational tools may generate standard deviation estimates that are a factor of five or more lower than the true standard deviation for a particular tally due to the inter-cycle correlations in the fission source.more » The magnitude of this under-prediction can climb as high as one hundred when combined with an ill-converged fission source or poor sampling techniques. Since Monte Carlo methods are widely used in reactor analysis (as a benchmarking tool) and criticality safety applications, an in-depth understanding of the effects of these issues must be developed in order to support the practical use of Monte Carlo software packages. A rigorous statistical analysis of localized tally results in eigenvalue calculations is presented using the SCALE/KENO-VI and MCNP Monte Carlo codes. The purpose of this analysis is to investigate the under-prediction in the uncertainty and its sensitivity to problem characteristics and calculational parameters, and to provide a comparative study between the two codes with respect to this under-prediction. It is shown herein that adequate source convergence along with proper specification of Monte Carlo parameters can reduce the magnitude of under-prediction in the uncertainty to reasonable levels; below a factor of 2 when inter-cycle correlations in the fission source are not a significant factor. In addition, through the use of a modified sampling procedure, the effects of inter-cycle correlations on both the mean value and standard deviation estimates can be isolated.« less