Development of a human reliability analysis (HRA) guide for qualitative analysis with emphasis on narratives and models for tasks in extreme conditions

Kirimoto, Yukihiro; Hirotsu, Yuko; Nonose, Kohei; Sasou, Kunihide

doi:10.1016/j.net.2020.10.004

Cited by 7 publications

(3 citation statements)

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“…These would include the consideration of the different stress levels, habitability issues, the degree of operator training and operator readiness to react in a proper manner" Chatri et al (2018). Kirimoto et al (2021) expands upon this, stating that "it is necessary in HRA to identify a realistic context for qualitative analyses, which thus points out the importance of […] representing how tasks in an accident scenario are affected by various factors, such as plant conditions (speed of accident progression, equipment availability, etc. ), operational procedures including cognition, and human-machine interfaces."…”

Section: Incorporation Of Other Parameters Including Pifsmentioning

confidence: 99%

“…Park et al (2015) also utilized seismic intensity to estimate HEP and reaction times for human operators, and yielded an HEP multiplier range for different seismic scenarios. Kirimoto et al (2021) identified the importance of creating a qualitative HRA model that included factors that affected task performance in addition to traditional quantitative methods, incorporating Performance Shaping Factors (PSFs) into the external events HRA. Kang and Seong (2022) developed a PSF taxonomy for extreme external events, improving on the limitations of existing taxonomies from HRA models such as THERP.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Seismic Events on Human Reliability and Phoenix HRA Methodology

Cosmin-Spanoche,

Ramos,

Mosleh

et al. 2023

Proceeding of the 33rd European Safety and Reliability Conference

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Risk assessment of Nuclear Power Plants (NPPs) through Probabilistic Risk Assessment (PRA) and Human Reliability Analysis (HRA) is relatively mature for internal events -those that start inside the power plant it serves. Advances have also been made for external events, such as earthquakes and floods. Yet, particularly for HRA, more research is needed to understand the impact of seismic events on human performance and the adequacy of currently used HRA methods. According to a report from the International Atomic Energy Agency, around 20 percent of nuclear reactors worldwide operate in areas vulnerable to earthquakes, so understanding seismic impacts on HRA is significant to prevent human errors and for realistic Human Error Probability (HEP) assessment.Seismic events may add failure modes and human and organizational factors that are not fully addressed by internal event models. This paper will investigate the unique factors associated with seismic events, and how they can be incorporated in the Phoenix HRA Methodology.

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Section: Incorporation Of Other Parameters Including Pifsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Impact of Seismic Events on Human Reliability and Phoenix HRA Methodology

Cosmin-Spanoche,

Ramos,

Mosleh

et al. 2023

Proceeding of the 33rd European Safety and Reliability Conference

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show abstract

“…5 Now, two generations of the HRA methods have been established (the third generation is under development). To reduce the accidents linked with human errors, they have been extensively utilized in various industries, including nuclear, [6][7][8] aerospace, 9 chemical, 10 healthcare, 11 and other safety-critical industries. 12 The first phase of the HRA was developed roughly from the late 1970s to the early 1990s.…”

Section: Introductionmentioning

confidence: 99%

An HFM‐CREAM model for the assessment of human reliability and quantification

Lin

Huang

2022

Quality & Reliability Eng

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Human reliability analysis (HRA) is a proactive approach to model and evaluate systematic human errors and has been extensively implemented in various complicated systems. The assessment of human errors relies heavily on the knowledge and experience of experts in real‐world cases. Moreover, there are usually specific sorts of uncertainty while experts use linguistic labels to evaluate human failure events. In this context, this paper seeks to establish a new model based on the hesitant fuzzy matrix (HFM) and the cognitive reliability and error analysis method (CREAM) to conduct a quantitative analysis of human errors. This model handles the multiple crisp scores of the common performance conditions (CPCs) given by experts according to the context description in terms of CPCs, determines the weights of CPCs by the HFM, and elicits the human error probability (HEP) point estimation formula considering consequences based on the CREAM. Finally, the effectiveness and practicality of the presented HFM‐CREAM model are demonstrated through the emergency response analysis of the steam generator tube rupture (SGTR) in nuclear power plant.

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