Evaluation of Human Reliability Analysis Methods Against Good Practices (NUREG-1842)

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Publication Information

Manuscript Completed: August 2006
Date Published: September 2006

Prepared by:
J. Forester, Sandia National Laboratories
A. Kolaczkowski, Science Applications International Corporation
E. Lois, U.S. Nuclear Regulatory Commission
D. Kelly, Science Applications International Corporation

Sandia National Laboratories
P.O. Box 58000, MS-0748
Albuquerque, NM 87185

Science Applications International Corporation
405 Urban Street, Suite 400
Lakewood, CO 80220

E. Lois, NRC Project Manager

Prepared for:
Division of Risk Assessment and Special Projects
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

Job Code Number Y6497

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Abstract

The U.S. Nuclear Regulatory Commission (NRC) has developed guidance for performing or evaluating human reliability analyses (HRAs) to support risk-informed regulatory decision-making and, in particular, the implementation of Regulatory Guide 1.200, "An Approach for Determining the Technical Adequacy of Probabilistic Risk Assessment Results for Risk-Informed Activities," dated February 2004. The NRC's detailed HRA guidance was developed in two phases. The first phase focused on developing "Good Practices for Implementing Human Reliability Analysis," as documented in NUREG-1792, dated April 2005. The second phase, summarized in this report, evaluated the various HRA methods that are commonly used in regulatory applications in the United States, with a particular focus on the extent to which they provide guidance to satisfy the good practices. Since the good practices closely parallel the requirements of the Probabilistic Risk Assessment (PRA) Standard (RA-S-2002) promulgated by the American Society of Mechanical Engineers (ASME), the HRA methods are also evaluated against that standard by implication. Toward that end, this report includes observations regarding the respective strengths and limitations of the HRA methods, as well as summaries of the scope, underlying knowledge base, and sources of quantification data associated with each method.