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HUMAN FAILURE EVENT DEPENDENCE [electronic resource] : WHAT ARE THE LIMITS

Published
Washington, D.C. : United States. Office of the Assistant Secretary for Nuclear Energy, 2016.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
Additional Creators
Idaho National Laboratory, United States. Office of the Assistant Secretary for Nuclear Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
Abstract Objectives: This paper discusses the differences between classical human reliability analysis (HRA) dependence and the full spectrum of probabilistic dependence. Positive influence suggests an error increases the likelihood of subsequent errors or success increases the likelihood of subsequent success. Currently the typical method for dependence in HRA implements the Technique for Human Error Rate Prediction (THERP) positive dependence equations. This assumes that the dependence between two human failure events varies at discrete levels between zero and complete dependence (as defined by THERP). Dependence in THERP does not consistently span dependence values between 0 and 1. In contrast, probabilistic dependence employs Bayes Law, and addresses a continuous range of dependence. Methods: Using the laws of probability, complete dependence and maximum positive dependence do not always agree. Maximum dependence is when two events overlap to their fullest amount. Maximum negative dependence is the smallest amount that two events can overlap. When the minimum probability of two events overlapping is less than independence, negative dependence occurs. For example, negative dependence is when an operator fails to actuate Pump A, thereby increasing his or her chance of actuating Pump B. The initial error actually increases the chance of subsequent success. Results: Comparing THERP and probability theory yields different results in certain scenarios; with the latter addressing negative dependence. Given that most human failure events are rare, the minimum overlap is typically 0. And when the second event is smaller than the first event the max dependence is less than 1, as defined by Bayes Law. As such alternative dependence equations are provided along with a look-up table defining the maximum and maximum negative dependence given the probability of two events. Conclusions: THERP dependence has been used ubiquitously for decades, and has provided approximations of the dependencies between two events. Since its inception, computational abilities have increased exponentially, and alternative approaches that follow the laws of probability dependence need to be implemented. These new approaches need to consider negative dependence and identify when THERP output is not appropriate.
Report Numbers
E 1.99:inl/con-16-38025
inl/con-16-38025
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Note
Published through SciTech Connect.
10/01/2016.
"inl/con-16-38025"
Probabilistic Safety Assessment and Management (PSAM 13), Seoul, Korea, October 2–7, 2016.
Sarah M. Herberger; Ronald L. Boring.
Funding Information
DE-AC07-05ID14517
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