skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Alternative Implementations of the Monte Carlo Power Method

Abstract

We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency.

Authors:
 [1];  [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP)
OSTI Identifier:
793906
Report Number(s):
ANL-01/15
TRN: US0201070
DOE Contract Number:  
W-31-109-ENG-38
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 18 Mar 2002
Country of Publication:
United States
Language:
English
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 97 MATHEMATICS AND COMPUTING; ALGORITHMS; CRITICALITY; EFFICIENCY; EIGENVALUES; FISSION; SAFETY ANALYSIS; MONTE CARLO METHOD; POWER DISTRIBUTION; Nuclear Criticality Safety Program (NCSP); Nominal Efficiencies; Fission Process; Supergeneration; Eigenvalues

Citation Formats

Blomquist, R. N., and Gelbard, E. M. Alternative Implementations of the Monte Carlo Power Method. United States: N. p., 2001. Web. doi:10.2172/793906.
Blomquist, R. N., & Gelbard, E. M. Alternative Implementations of the Monte Carlo Power Method. United States. https://doi.org/10.2172/793906
Blomquist, R. N., and Gelbard, E. M. 2001. "Alternative Implementations of the Monte Carlo Power Method". United States. https://doi.org/10.2172/793906. https://www.osti.gov/servlets/purl/793906.
@article{osti_793906,
title = {Alternative Implementations of the Monte Carlo Power Method},
author = {Blomquist, R. N. and Gelbard, E. M.},
abstractNote = {We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency.},
doi = {10.2172/793906},
url = {https://www.osti.gov/biblio/793906}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Dec 01 00:00:00 EST 2001},
month = {Sat Dec 01 00:00:00 EST 2001}
}