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Report on some methods of determining the state of convergence of Monte Carlo risk estimates

Abstract

The Department of the Environment is developing a methodology for assessing potential sites for the disposal of low and intermediate level radioactive wastes. Computer models are used to simulate the groundwater transport of radioactive materials from a disposal facility back to man. Monte Carlo methods are being employed to conduct a probabilistic risk assessment (pra) of potential sites. The models calculate time histories of annual radiation dose to the critical group population. The annual radiation dose to the critical group in turn specifies the annual individual risk. The distribution of dose is generally highly skewed and many simulation runs are required to predict the level of confidence in the risk estimate i.e. to determine whether the risk estimate is converged. This report describes some statistical methods for determining the state of convergence of the risk estimate. The methods described include the Shapiro-Wilk test, calculation of skewness and kurtosis and normal probability plots. A method for forecasting the number of samples needed before the risk estimate is converged is presented. Three case studies were conducted to examine the performance of some of these techniques. (author).
Publication Date:
May 01, 1991
Product Type:
Technical Report
Report Number:
DOE-HMIP-RR-91-015; PECD-7-9-226.
Reference Number:
SCA: 052002; PA: AIX-23:005805; SN: 91000616022
Resource Relation:
Other Information: PBD: May 1991
Subject:
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE WASTES FROM NUCLEAR FACILITIES; GROUND WATER; RADIONUCLIDE MIGRATION; ROCK-FLUID INTERACTIONS; UNDERGROUND DISPOSAL; INTERMEDIATE-LEVEL RADIOACTIVE WASTES; RADIOACTIVE WASTE DISPOSAL; LOW-LEVEL RADIOACTIVE WASTES; RISK ASSESSMENT; CONVERGENCE; MONTE CARLO METHOD; ANNUAL LIMIT OF INTAKE; COMPUTERIZED SIMULATION; CONTAMINATION; HYDRAULIC CONDUCTIVITY; PROBABILITY; STATISTICS; UNITED KINGDOM ORGANIZATIONS; 052002; WASTE DISPOSAL AND STORAGE
OSTI ID:
10102493
Research Organizations:
Department of the Environment, London (United Kingdom). Her Majesty`s Inspectorate of Pollution
Country of Origin:
United Kingdom
Language:
English
Other Identifying Numbers:
Other: ON: DE92611977; CNN: Contract 3097/TR-28; TRN: GB9104251005805
Availability:
OSTI; NTIS (US Sales Only); INIS
Submitting Site:
GBN
Size:
45 p.
Announcement Date:
Jun 30, 2005

Citation Formats

Orford, J L, Hufton, D, and Johnson, K. Report on some methods of determining the state of convergence of Monte Carlo risk estimates. United Kingdom: N. p., 1991. Web.
Orford, J L, Hufton, D, & Johnson, K. Report on some methods of determining the state of convergence of Monte Carlo risk estimates. United Kingdom.
Orford, J L, Hufton, D, and Johnson, K. 1991. "Report on some methods of determining the state of convergence of Monte Carlo risk estimates." United Kingdom.
@misc{etde_10102493,
title = {Report on some methods of determining the state of convergence of Monte Carlo risk estimates}
author = {Orford, J L, Hufton, D, and Johnson, K}
abstractNote = {The Department of the Environment is developing a methodology for assessing potential sites for the disposal of low and intermediate level radioactive wastes. Computer models are used to simulate the groundwater transport of radioactive materials from a disposal facility back to man. Monte Carlo methods are being employed to conduct a probabilistic risk assessment (pra) of potential sites. The models calculate time histories of annual radiation dose to the critical group population. The annual radiation dose to the critical group in turn specifies the annual individual risk. The distribution of dose is generally highly skewed and many simulation runs are required to predict the level of confidence in the risk estimate i.e. to determine whether the risk estimate is converged. This report describes some statistical methods for determining the state of convergence of the risk estimate. The methods described include the Shapiro-Wilk test, calculation of skewness and kurtosis and normal probability plots. A method for forecasting the number of samples needed before the risk estimate is converged is presented. Three case studies were conducted to examine the performance of some of these techniques. (author).}
place = {United Kingdom}
year = {1991}
month = {May}
}