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Review of advances in human reliability analysis of errors of commission-Part 2: EOC quantification

机译:人类对佣金错误的可靠性分析的进展的回顾-第2部分:EOC量化

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In close connection with examples relevant to contemporary probabilistic safety assessment (PSA), a review of advances in human reliability analysis (HRA) of post-initiator errors of commission (EOCs), i.e. inappropriate actions under abnormal operating conditions, has been carried out. The review comprises both EOC identification (part 1) and quantification (part 2); part 2 is presented in this article. Emerging HRA methods in this field are: ATHEANA, MERMOS, the EOC HRA method developed by Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS), the MDTA method and CREAM. The essential advanced features are on the conceptual side, especially to envisage the modeling of multiple contexts for an EOC to be quantified (ATHEANA, MERMOS and MDTA), in order to explicitly address adverse conditions. There is promising progress in providing systematic guidance to better account for cognitive demands and tendencies (GRS, CREAM), and EOC recovery (MDTA). Problematic issues are associated with the implementation of multiple context modeling and the assessment of context-specific error probabilities. Approaches for task or error opportunity scaling (CREAM, GRS) and the concept of reference cases (ATHEANA outlook) provide promising orientations for achieving progress towards data-based quantification. Further development work is needed and should be carried out in close connection with large-scale applications of existing approaches.
机译:与与现代概率安全评估(PSA)相关的示例紧密相关,已对启动后提成错误(EOC)的人类可靠性分析(HRA)的进展进行了回顾,即在异常操作条件下的不当行为。审查包括EOC识别(第1部分)和量化(第2部分);本文介绍了第2部分。该领域新兴的HRA方法有:ATHEANA,MERMOS,由Gesellschaft fuer Anlagen- und Reaktorsicherheit(GRS)开发的EOC HRA方法,MDTA方法和CREAM。基本的高级功能是在概念方面,尤其是为要量化的EOC(ATHEANA,MERMOS和MDTA)设想多个上下文的建模,以便明确解决不利条件。在提供系统指导以更好地说明认知需求和倾向(GRS,CREAM)和EOC恢复(MDTA)方面,有望取得进展。有问题的问题与多个上下文建模的实现以及特定于上下文的错误概率的评估相关。任务或错误机会缩放的方法(CREAM,GRS)和参考案例的概念(ATHEANA展望)为实现基于数据的量化的进展提供了有希望的方向。需要进一步的开发工作,并且应与现有方法的大规模应用紧密结合进行。

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