A study on quantification for the impact of stress and time margin on human error probability assessment in nuclear power plant using fuzzy inference

After the Fukushima Daiichi Nuclear Power Station Accident in 2011, there has been a significant enhancement in Probabilistic Risk Assessment (PRA), including Human Reliability Assessment (HRA) for tasks performed under extreme conditions. This includes responses to external events and operations using portable mitigation equipment. As a result, HRA now necessitates estimates of various work environments, such as outdoor work in an environment affected by an external event, and those performed mainly in the main control room. This shift in focus underscores the increasing importance of understanding the specific situations in which operators perform tasks. For example, when operators carry out a task under radiation conditions, they experience increased stress and require more time to complete the task. However, it is challenging to quantitatively evaluate the impact of these parameters on the human error probability (HEP). Especially in a multi-unit site, the dependencies between units lead to unique environmental changes in the working area, making it necessary to develop a method for estimating the HEP. Therefore, this study utilizes the dynamic master logic diagram and the fuzzy inference method to assess the HEP, taking into account the evolving context during a severe accident scenario in a multi-unit system. Additionally, it examines the influence of operator skills and the manual's readability on the HEP through fuzzy inference. Consequently, the study suggests a method to estimate complexity between PSF changes and HEP increase quantitatively under various stress and time margin conditions, also considering the operator's skill level and the manual's readability.