Human reliability analysis studies from simulator experiments using Bayesian inference

Garg, Vipul; Vinod, Gopika; Prasad, Mahendra; Chattopadhyay, J.; Smith, Curtis; Kant, Vivek

doi:10.1016/j.ress.2022.108846

Title: Human reliability analysis studies from simulator experiments using Bayesian inference

Journal Article · Mon Sep 19 00:00:00 EDT 2022 · Reliability Engineering and System Safety

DOI:https://doi.org/10.1016/j.ress.2022.108846· OSTI ID:1909241

^[1]; Vinod, Gopika ^[1]; Prasad, Mahendra ^[1]; Chattopadhyay, J. ^[1];

^[2]; Kant, Vivek ^[3]

Bhabha Atomic Research Centre (BARC), Mumbai (India)
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Indian Inst. of Technology (IIT), Mumbai (India)

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

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Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: DE-AC07-05ID14517

OSTI ID:: 1909241

Report Number(s):: INL/JOU-22-69374-Rev000; TRN: US2312108

Journal Information:: Reliability Engineering and System Safety, Vol. 229; ISSN 0951-8320

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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