A method for systematically developing the knowledge base of reactor operators in nuclear power plants to support cognitive modeling of operator performance

Yunfei Zhao and Carol Smidts

Reliability Engineering and System Safety, 2019, vol. 186, issue C, 64-77

Abstract: Methods based on cognitive modeling have attracted increasing attention in the human reliability analysis community. In such methods, the operator knowledge base plays a central role. This paper proposes a method for systematically developing the knowledge base of nuclear power plant operators. The method starts with a systematic literature review of a predefined topic. Then, the many collected publications are reduced to summaries. Relevant knowledge is then extracted from the summaries using an improved qualitative content analysis method to generate a large number of pieces of knowledge. Lastly, the pieces of knowledge are integrated in a systematic way to generate a knowledge graph consisting of nodes and links. As a case study, the proposed method is applied to develop the knowledge base of reactor operators pertaining to severe accidents in nuclear power plants. The results show that the proposed method exhibits advantages over conventional methods, including reduced reliance on expert knowledge and improved traceability of the process. Generalization of the proposed method to other sources of materials and application of the knowledge base are also discussed. Although this paper is focused on nuclear applications, the proposed method may be extended to other industrial sectors with little additional effort.

Keywords: Knowledge base development; Cognitive modeling; Human reliability analysis; Nuclear power plant; Severe accident (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:186:y:2019:i:c:p:64-77

DOI: 10.1016/j.ress.2019.02.014

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