PSAM 16 - Paper Overview

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Lead Author: Jinkyun Park Co-author(s): Inseok Jang, isjang@kaeri.re.kr Jooyoung Park, jooyoung.Park@inl.gov Ronald L. Boring, Ronald.Boring@inl.gov Thomas A. Ulrich, thomas.ulrich@inl.gov

A framework to integrate HRA data obtained from different sources based on the complexity scores of proceduralized tasks
Since the TMI accident, it is evident that the PSA (Probabilistic Safety Assessment) or PRA (Probabilistic Risk Assessment) has been used as one of the representative techniques to enhance the safety of nuclear power plants (NPPs) by visualizing the catalog of potential hazards in a systematic way. Since human error represents one of the potential hazards, diverse HFEs (Human Failure Events) should be incorporated into the development of the PSA model. Typical HFEs include “the purpose of the task cannot be achieved” or “the task fails to be completed” [1]. Accordingly, in terms of conducting the PSA, it is indispensable to quantify the likelihood of HFEs (or Human Error Probabilities, HEPs). For this reason, many kinds of HRA (Human Reliability Analysis) methods have been proposed in the last several decades. In general, the HRA process can be done with three steps: (1) task analysis, (2) qualitative analysis, and (3) quantitative analysis. Brief explanations on these steps are as follows: “Task analysis is the process of collecting and analyzing relevant information on the major human actions considered in a PSA model. In qualitative analysis, performance shaping factors (PSFs) critical to error occurrences are analyzed in the context of each human action. PSFs refer to factors that influence human performance, including experience, stress, and task complexity. Lastly, based on the task analysis and qualitative analysis results, HEPs are estimated using quantitative analysis [2].” From this excerpt, it is obvious that the quality of information to be used in the HRA process (i.e., HRA data) is critical for ensuring the credibility of HRA results. This became the motivation of HRA data collection from many available sources including event investigation reports and simulator studies [3]. Unfortunately, it is also true that the quality of HRA data is one of the key limitations from the very beginning of an HRA method development [4, 5], it is critical to materialize how to soundly integrate a lot of HRA data spread out in the diverse sources. In order to address this issue, in this study, the framework of HRA data integration is investigated based on the complexity of proceduralized tasks. The underlying idea is to directly compare two sets of HRA data obtained from different sources (one came from the full-scope training simulator of NPPs and the other from a small-scale laboratory experiment using a simplified simulator such as INL’s Rancor Microworld). If there is a significant correlation between two sets of HRA data, then it is expected that we can have a relevant clue supporting how to integrate diverse HRA data. [1] Kirimoto, Y., Hirotsu, Y., Nonose, K., and Sasou K., 2021. Development of a human reliability analysis (HRA) guide for qualitative analysis with emphasis on narratives and models for tasks in extreme conditions, 53(2), p. 376-385 (https://doi.org/10.1016/j.net.2020.10.004) [2] Park, J., Boring, R. L., Ulrich, T. A., Lew, R., Lee, S., Park, B., and Kim, J., 2022. A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators, Reliability Engineering and System Safety, 221, 108326 (https://doi.org/10.1016/j.ress.2022.108326) [3] Park, J., Jung, W., Kim, S., Choi, S. Y., Kim, Y., Lee, S. J., Yang, J. E., and Dang, V. N., 2014. A guideline to collect HRA data in the simulator of nuclear power plants, Korea Atomic Energy Research Institute, KAERI/TR-5206, Daejeon, Republic of Korea (written in English) [4] Swain, A. D., 1990. Human reliability analysis: Need, status, trends and limitations, Reliability Engineering and System Safety, 29(3), p. 301-313 (https://doi.org/10.1016/0951-8320(90)90013-D) [5] Hollnagel, E., 2005. Human reliability assessment in context, Nuclear Engineering and Technology, 37(2), p. 159-166

A framework to integrate HRA data obtained from different sources based on the complexity scores of proceduralized tasks

Since the TMI accident, it is evident that the PSA (Probabilistic Safety Assessment) or PRA (Probabilistic Risk Assessment) has been used as one of the representative techniques to enhance the safety of nuclear power plants (NPPs) by visualizing the catalog of potential hazards in a systematic way. Since human error represents one of the potential hazards, diverse HFEs (Human Failure Events) should be incorporated into the development of the PSA model. Typical HFEs include “the purpose of the task cannot be achieved” or “the task fails to be completed” [1]. Accordingly, in terms of conducting the PSA, it is indispensable to quantify the likelihood of HFEs (or Human Error Probabilities, HEPs). For this reason, many kinds of HRA (Human Reliability Analysis) methods have been proposed in the last several decades. In general, the HRA process can be done with three steps: (1) task analysis, (2) qualitative analysis, and (3) quantitative analysis. Brief explanations on these steps are as follows: “Task analysis is the process of collecting and analyzing relevant information on the major human actions considered in a PSA model. In qualitative analysis, performance shaping factors (PSFs) critical to error occurrences are analyzed in the context of each human action. PSFs refer to factors that influence human performance, including experience, stress, and task complexity. Lastly, based on the task analysis and qualitative analysis results, HEPs are estimated using quantitative analysis [2].” From this excerpt, it is obvious that the quality of information to be used in the HRA process (i.e., HRA data) is critical for ensuring the credibility of HRA results. This became the motivation of HRA data collection from many available sources including event investigation reports and simulator studies [3]. Unfortunately, it is also true that the quality of HRA data is one of the key limitations from the very beginning of an HRA method development [4, 5], it is critical to materialize how to soundly integrate a lot of HRA data spread out in the diverse sources. In order to address this issue, in this study, the framework of HRA data integration is investigated based on the complexity of proceduralized tasks. The underlying idea is to directly compare two sets of HRA data obtained from different sources (one came from the full-scope training simulator of NPPs and the other from a small-scale laboratory experiment using a simplified simulator such as INL’s Rancor Microworld). If there is a significant correlation between two sets of HRA data, then it is expected that we can have a relevant clue supporting how to integrate diverse HRA data. [1] Kirimoto, Y., Hirotsu, Y., Nonose, K., and Sasou K., 2021. Development of a human reliability analysis (HRA) guide for qualitative analysis with emphasis on narratives and models for tasks in extreme conditions, 53(2), p. 376-385 (https://doi.org/10.1016/j.net.2020.10.004) [2] Park, J., Boring, R. L., Ulrich, T. A., Lew, R., Lee, S., Park, B., and Kim, J., 2022. A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators, Reliability Engineering and System Safety, 221, 108326 (https://doi.org/10.1016/j.ress.2022.108326) [3] Park, J., Jung, W., Kim, S., Choi, S. Y., Kim, Y., Lee, S. J., Yang, J. E., and Dang, V. N., 2014. A guideline to collect HRA data in the simulator of nuclear power plants, Korea Atomic Energy Research Institute, KAERI/TR-5206, Daejeon, Republic of Korea (written in English) [4] Swain, A. D., 1990. Human reliability analysis: Need, status, trends and limitations, Reliability Engineering and System Safety, 29(3), p. 301-313 (https://doi.org/10.1016/0951-8320(90)90013-D) [5] Hollnagel, E., 2005. Human reliability assessment in context, Nuclear Engineering and Technology, 37(2), p. 159-166

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Lead Author Name: Jinkyun Park (kshpjk@kaeri.re.kr)

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Country: South Korea
Company: Korea Atomic Energy Research Institute
Job Title: Principal Researcher

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

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