Abstract
A human’s knowledge base is a key component for the development of a mechanistic model of human response to be used for human reliability analysis. This paper proposes a new method for constructing this knowledge base. The proposed method is comprised of three steps: (1) systematic literature review, which is used to collect data pertinent to the subject under study; (2) summarization, the goal of which is to extract key points that are expressed in the literature; (3) qualitative coding, a process in which codes closely related to the topic are derived and the relationships between these codes are expressed. As a case study, the proposed method is being applied to construct an operator’s knowledge base concerning severe accident phenomenology in a nuclear power plant. Part of this application is explored in this paper. With the proposed method and the resulting knowledge base, it is expected that an individual’s response when presented with a specific context can be modeled in more detail.
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References
Meshkati, N.: Human factors in large-scale technological systems’ accidents: three mile Island, Bhopal. Chernobyl Ind. Crisis Q. 5(2), 133–154 (1991)
Swain, A.D., Guttmann, H.E.: Handbook of human-reliability analysis with emphasis on nuclear power plant applications. Final report, Sandia National Labs., Albuquerque, NM, USA (1983)
Gertman, D., Blackman, H., Marble, J., Byers, J., Smith, C.: The SPAR-H Human Reliability Analysis Method. US Nuclear Regulatory Commission (2005)
Smidts, C., Shen, S.H., Mosleh, A.: The IDA cognitive model for the analysis of nuclear power plant operator response under accident conditions. part I: problem solving and decision making model. Reliab. Eng. Syst. Saf. 55(1), 51–71 (1997)
Chang, Y.H., Mosleh, A.: Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents: part 1: overview of the IDAC model. Reliab. Eng. Syst. Saf. 92(8), 997–1013 (2007)
Li, Y.: Modeling and simulation of operator knowledge-based behavior. Ph.D. dissertation, University of Maryland, College Park (2013)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cybern. SMC 15(1), 116–132 (1985)
Kitchenham, B., Brereton, O.P., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering–a systematic literature review. Inf. Softw. Technol. 51(1), 7–15 (2009)
Kitchenham, B.: Procedures for performing systematic reviews. Technical report, Keele University (2004)
Huang, F., Smidts, C.: Causal mechanism graph – a new notation for capturing cause-effect knowledge in software dependability. Reliab. Eng. Syst. Saf. 158, 196–212 (2017)
Hsieh, H.F., Shannon, S.E.: Three approaches to qualitative content analysis. Qual. Health Res. 15(9), 1277–1288 (2005)
Elo, S., Kyngäs, H.: The qualitative content analysis process. J. Adv. Nurs. 62(1), 107–115 (2008)
Dick, J.E., Nath, V.I., Kohn, E., Min, T.K., Prawirosoehardjo, S.: Event sequence of a severe accident in a single-unit CANDU reactor. Nucl. Technol. 90(2), 155–167 (1990)
Anderson, J.R.: A spreading activation theory of memory. J. Verbal Learn. Verbal Behav. 22(3), 261–295 (1983)
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This research is funded by U.S. Nuclear Regulatory Commission under Grant NRC-HQ-60-15-G-0002.
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Zhao, Y., Altman, K., Chaudhury, K., Anandika, M., Smidts, C. (2018). A Systematic Method to Build a Knowledge Base to be Used in a Human Reliability Analysis Model. In: Boring, R. (eds) Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2017. Advances in Intelligent Systems and Computing, vol 589. Springer, Cham. https://doi.org/10.1007/978-3-319-60645-3_6
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DOI: https://doi.org/10.1007/978-3-319-60645-3_6
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