Accession Number:

ADA516015

Title:

A Probabilistic Approach to Uncertainty Analysis in NTPR Radiation Dose Assessments

Descriptive Note:

Technical rept.

Corporate Author:

SCIENCE APPLICATIONS INC MCLEAN VA

Report Date:

2009-11-01

Pagination or Media Count:

266.0

Abstract:

Summaries of the individual sections of this report are provided in this executive summary. Each heading within this summary is labeled with the section number of the narrative report for easy reference to additional details and discussion. Introduction 1 and Background 2 In October 2007, the Veterans Advisory Board on Dose Reconstruction VBDR recommended that the Nuclear Test Personnel Review NTPR Program develop procedures to perform probabilistic uncertainty analyses for Radiation Dose Assessments RDAs VBDR, 2007. Specifically, the NTPR standard operating procedures should specify whether uncertainty estimates from individual sources are independent or correlated and when and how uncertainties should be propagated. The Defense Threat Reduction Agency DTRA tasked Science Applications International Corporation SAIC to investigate methods that could be used for conducting analyses for NTPR RDAs DTRA, 2007b. In response, SAIC identified the efforts main goal to develop and demonstrate a methodology and its enabling computational tools to perform probabilistic radiation dose assessments for NTPR atomic veterans. The objectives identified for the study are addressed in Section 1. The NTPR Programs reconstructed radiation doses for atomic veterans have traditionally employed methods using high-sided estimates for parameters that are difficult to characterize, but were considered to overestimate actual doses and therefore provided reliable upper bounds. In a 2003 review of DTRAs dose reconstruction program, a committee of the National Research Council of the National Academy of Sciences NASNRC concluded that although central estimates of reconstructed doses for external gamma exposures were valid in most cases, upper bounds could not always be shown to be at least as great as a 95 percent upper confidence limit NRC, 2003.

Subject Categories:

  • Statistics and Probability
  • Chemical, Biological and Radiological Warfare

Distribution Statement:

APPROVED FOR PUBLIC RELEASE