Capturing cognitive causal paths in human reliability analysis with Bayesian network models

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• 作者：Kilian Zwirglmaier^a ; ^{kilian.zwirglmaier@tum.de} ; Daniel Straub^a ; ; Katrina M. Groth^b
• 关键词：ACRS ; Advisory Committee on Reactor Safeguards ; ATHEANA ; A Technique for Human Event Analysis ; BN ; Bayesian Network ; CFM ; Crew Failure Mode ; CPT ; Conditional Probability Table ; DAG ; Directed Acyclic Graph ; DT ; Decision Tree ; HEP ; Human Error Probability ; HFE ; Human Failure Event ; HRA ; Human Reliability Assessment ; HSI ; Human-System Interface ; IDHEAS ; Integrated Decision-Tree Human Event Analysis System ; NRC ; Nuclear Regulatory Commission ; PDF ; Probability Density Function ; PIF ; Performance Influ
• 刊名：Reliability Engineering & System Safety
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：158
• 期：Complete
• 页码：117-129
• 全文大小：1767 K
• 卷排序：158

文摘

A framework for building traceable BNs for HRA, based on cognitive causal paths. A qualitative BN structure, directly showing these causal paths is developed. Node reduction algorithms are used for making the BN structure quantifiable. BN quantified through expert estimates and observed data (Bayesian updating). The framework is illustrated for a crew failure mode of IDHEAS.