BibTeX

@inproceedings{Mosleh2012,
title = {A Model-Based Human Reliability Analysis Methodology},
author = {Ali Mosleh and Song-Hua Shen and Dana L Kelly and Johanna H Oxstrand and Katrina Groth},
year = {2012},
date = {2012-06-01},
booktitle = {Proceedings of the International Conference on Probabilistic Safety Assessment and Management (PSAM 11)},
address = {Helsinki, Finland},
abstract = {This paper provides an overview of a comprehensive framework, corresponding set of techniques, and guidelines for performing HRA analysis in various nuclear power plant risk-informed applications such as full-power PRA and event assessment. The work on the methodology has been supported through a number of projects and grants sponsored by the US NRC. The qualitative analysis part of the approach introduces the “crew response tree” (CRT), providing a structure for capturing the context associated with the human failure events (HFE), including EOO and EOC. It also uses a team-centered version of the IDA model and “macro cognitive” abstractions of crew behavior, as well as other relevant findings from cognitive psychology and operating experience, in order to identify potential causes of failures and influencing factors during procedure-driven and knowledge-supported crew-plant interactions. The result of the analysis is the set of identified HFEs and the likely scenarios leading to each. The quantification methodology uses a conditional probability expression, associating the conditional probability of an HFE with probabilities of the contexts as given by PRA scenario, human failure mechanisms, and the underlying “performance influencing factors”. Such mathematical formulation can be used to directly estimate HEPs using various information sources (e.g., expert estimations, anchor values, simulator or historical data), or can be modified to interface with existing quantification approaches. In addition a fully integrated BBN based quantification option is presented for more explicit accounting of causal dependencies of crew response (such as dependence between HFEs). The development envisions software-supported quantitative analysis, to build and analyse CRTs, identify Crew Failure Modes (CFMs), develop the human failure scenarios, and to support a number of quantification options, including the BBN based approach. Two other papers in this conference provide the details of the qualitative analysis approach and an example.},
keywords = {causal models, crew failure modes, human error, Human Reliability Analysis (HRA), nuclear power},
pubstate = {published},
tppubtype = {inproceedings}
}

Abstract

This paper provides an overview of a comprehensive framework, corresponding set of techniques, and guidelines for performing HRA analysis in various nuclear power plant risk-informed applications such as full-power PRA and event assessment. The work on the methodology has been supported through a number of projects and grants sponsored by the US NRC. The qualitative analysis part of the approach introduces the “crew response tree” (CRT), providing a structure for capturing the context associated with the human failure events (HFE), including EOO and EOC. It also uses a team-centered version of the IDA model and “macro cognitive” abstractions of crew behavior, as well as other relevant findings from cognitive psychology and operating experience, in order to identify potential causes of failures and influencing factors during procedure-driven and knowledge-supported crew-plant interactions. The result of the analysis is the set of identified HFEs and the likely scenarios leading to each. The quantification methodology uses a conditional probability expression, associating the conditional probability of an HFE with probabilities of the contexts as given by PRA scenario, human failure mechanisms, and the underlying “performance influencing factors”. Such mathematical formulation can be used to directly estimate HEPs using various information sources (e.g., expert estimations, anchor values, simulator or historical data), or can be modified to interface with existing quantification approaches. In addition a fully integrated BBN based quantification option is presented for more explicit accounting of causal dependencies of crew response (such as dependence between HFEs). The development envisions software-supported quantitative analysis, to build and analyse CRTs, identify Crew Failure Modes (CFMs), develop the human failure scenarios, and to support a number of quantification options, including the BBN based approach. Two other papers in this conference provide the details of the qualitative analysis approach and an example.