United States Nuclear Regulatory Commission - Protecting People and the Environment

A Nonparametric Statistical Methodology for the Design and Analysis of Final Status Decommissioning Surveys - Interim Draft Report for Comment and Use (NUREG-1505, Revision 1)

This NUREG-series publication was issued as a draft report for public comment and interim use, and the comment period is now closed.

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Publication Information

Manuscript Completed: June 1998
Date Published: June 1998

Prepared by:
C.V. Gogolak*, G.E. Powers, A.M. Huffert

*Environmental Measurements Laboratory
U.S. Department of Energy
201 Varick Street, 5th Floor
New York, NY 10014

Division of Regulatory Applications
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

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Abstract

This report describes a nonparametric statistical methodology for the design and analysis of final status decommissioning surveys in support of the final rulemaking on Radiological Criteria for License Termination published by the Nuclear Regulatory Commission in the Federal Register on July 21, 1997. The techniques described are expected to be applicable to a broad range of circumstances, but do not preclude the use of alternative methods as particular situations may warrant. Nonparametric statistical methods for testing compliance with decommissioning criteria are provided both for the case in which the radionuclides of concern occur in background and also for the case in which they do not occur in background. The tests described are the Sign test, the Wilcoxon Rank Sum test, and a Quantile test. These tests are performed in conjunction with an Elevated Measurement Comparison to provide confidence that the radiological criteria specified for license termination are met. The Data Quality Objectives process is used for the planning of final site surveys. This includes methods for determining the number of samples needed to obtain statistically valid comparisons with decommissioning criteria and the methods for conducting the statistical tests with the resulting sample data.

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