Actions for An overview of the evolution of human reliability analysis in the context of probabilistic risk assessment [electronic resource].

Email RIS file
Bookmark
Report an Issue

An overview of the evolution of human reliability analysis in the context of probabilistic risk assessment [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy, 2009.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
45 pages : digital, PDF file
Additional Creators
Sandia National Laboratories, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
Free-to-read Unrestricted online access
Summary
Since the Reactor Safety Study in the early 1970's, human reliability analysis (HRA) has been evolving towards a better ability to account for the factors and conditions that can lead humans to take unsafe actions and thereby provide better estimates of the likelihood of human error for probabilistic risk assessments (PRAs). The purpose of this paper is to provide an overview of recent reviews of operational events and advances in the behavioral sciences that have impacted the evolution of HRA methods and contributed to improvements. The paper discusses the importance of human errors in complex human-technical systems, examines why humans contribute to accidents and unsafe conditions, and discusses how lessons learned over the years have changed the perspective and approach for modeling human behavior in PRAs of complicated domains such as nuclear power plants. It is argued that it has become increasingly more important to understand and model the more cognitive aspects of human performance and to address the broader range of factors that have been shown to influence human performance in complex domains. The paper concludes by addressing the current ability of HRA to adequately predict human failure events and their likelihood.
Report Numbers
E 1.99:sand2008-5085
sand2008-5085
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
01/01/2009.
"sand2008-5085"
Wreathall, John; Lois, Erasmia; Forester, John Alan; Cooper, Susan E.; Bley, Dennis C.; Kolaczkowski, Alan M.
Funding Information
AC04-94AL85000
View MARC record | catkey: 14800207