The use of the SACADA taxonomy to analyze simulation records: Insights and suggestions

John Park, Y.J. Chang, Y. Kim, S. Choi, S. Kim and W. Jung

Reliability Engineering and System Safety, 2017, vol. 159, issue C, 174-183

Abstract: It is evident that diverse human reliability analysis (HRA) methods are effective for enhancing the safety of socio-technical systems through identifying the most vulnerable tasks to human errors with the associated human error probabilities. This means that reliable human performance data is an important factor affecting HRA quality. Therefore, many researchers have developed technical underpinnings (such as guidelines and taxonomies) that specify what and how HRA data can be collected from simulator experiments. Here, SACADA (Scenario Authoring, Characterization, and Debriefing Application) taxonomy recently developed by US NRC (Nuclear Regulatory Commission) is worth emphasizing, because it is constructed on the basis of a cognitive model (i.e., a top-down approach) while most of the technical underpinnings are developed by a bottom-up approach (i.e., the intensive review of existing literature). For this reason, in this study, the SACADA taxonomy is used to analyze several audio-visual records collected from the full scope simulators of nuclear power plants in the Republic of Korea. The results indicate that the SACADA taxonomy is useful to collect operator performance data in simulator training for HRA. Certain human performance information that can be provided by SACADA data provided are difficult to be covered by the bottom-up approach.

Keywords: Nuclear power plant; Human reliability analysis; Simulator experiment; Data collection framework; SACADA taxonomy (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:159:y:2017:i:c:p:174-183

DOI: 10.1016/j.ress.2016.11.002

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