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Title: Statistical Tests for Convergence in Monte Carlo Criticality Calculations

Abstract

This report describes methods for using statistical tests to automatically determine convergence of Monte Carlo (MC) iterations in criticality calculations. The methods described herein are intended to replace the traditional approach used for the past 60 years: make a trial run; determine convergence based on plots of k-effective and Shannon entropy vs cycle; adjust the input parameters for controlling the iterations; make a final run to obtain results and statistics.

Authors:
 [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1471319
Report Number(s):
LA-UR-18-28764
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
MCNP; neutron transport

Citation Formats

Brown, Forrest B., and Martin, William Russell. Statistical Tests for Convergence in Monte Carlo Criticality Calculations. United States: N. p., 2018. Web. doi:10.2172/1471319.
Brown, Forrest B., & Martin, William Russell. Statistical Tests for Convergence in Monte Carlo Criticality Calculations. United States. doi:10.2172/1471319.
Brown, Forrest B., and Martin, William Russell. Fri . "Statistical Tests for Convergence in Monte Carlo Criticality Calculations". United States. doi:10.2172/1471319. https://www.osti.gov/servlets/purl/1471319.
@article{osti_1471319,
title = {Statistical Tests for Convergence in Monte Carlo Criticality Calculations},
author = {Brown, Forrest B. and Martin, William Russell},
abstractNote = {This report describes methods for using statistical tests to automatically determine convergence of Monte Carlo (MC) iterations in criticality calculations. The methods described herein are intended to replace the traditional approach used for the past 60 years: make a trial run; determine convergence based on plots of k-effective and Shannon entropy vs cycle; adjust the input parameters for controlling the iterations; make a final run to obtain results and statistics.},
doi = {10.2172/1471319},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {9}
}

Technical Report:

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