Human error probability estimation by coupling simulator data and deterministic analysis

Prasad, M. A.; Gaikwad, Avinash J.

doi:10.1016/j.pnucene.2015.01.008

Cited by 14 publications

(6 citation statements)

References 11 publications

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“…They found that selecting the wrong screen had the lowest probability of recovery failure while omitting operation selection and delaying operation had the highest probability of recovery failure [ 29 , 30 ]. Since data on human error probability in real CRs of NPPs is scarce, Prasad and Gaikwad proposed a method for estimating HEP by conducting specific accident scenarios in simulators, emphasizing the importance of scenario-specific data for reliable reliability analysis [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

Looking beyond the screen: A systematic review of safety in control rooms

Janizadeh,

Choobineh,

Charkhabi

et al. 2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

Looking beyond the screen: A systematic review of safety in control rooms

Janizadeh,

Choobineh,

Charkhabi

et al. 2024

Heliyon

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“…Refs. 22 has categorized human error into three groups: (1) Group “A”: actions during maintenance that can cause equipment malfunction; (2) Group “B”: errors that affect the start of events; (3) Group “C”: errors related to the operator's response to an accident. Group A: Colombia's blackout in 2007 left about 41,000,000 people without power for 4.5 h. The cause of the event was a human error while correcting maintenance of a protective device in a 230 kV substation 11 …”

Section: Background and The Related Workmentioning

confidence: 99%

Estimating and ranking the impact of human error roots on power grid maintenance group based on a combination of mathematical expectation, Shannon entropy, and TOPSIS

Tavakoli

Nafar

2021

Quality & Reliability Eng

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Due to the importance of electrical grid reliability, analysis and evaluation of human error in the maintenance of electrical networks should be also considered seriously. The root causes of these errors must be identified and prioritized to plan for human error reduction. One of the objectives of the present study is to identify and predict these roots for power transmission maintenance groups from organizational, job position, communication, individual, and supervision aspects along with the relationships between these factors. In particular, this paper demonstrates that supervisor behavior as an external factor has a significant effect on maintenance personnel error. For this reason, special attention has been paid to identifying and controlling human factors from a supervisory point of view in this study. This paper also provides a method for detecting the extent of the expected influence of these roots on each personnel, since human error has a random nature. This is done based on the law of mathematical expectation. Finally, a method is suggested to rank roots based on greater effectiveness and evaluate personnel with higher error expectations. The proposed method is a combination of intermediate methods, Shannon entropy, and technique for order of preference by similarity to ideal solution (TOPSIS). The origins of the four human errors between 2014 and 2018 related to the two experts of Fars Electricity Maintenance Contractor Company are compared by the proposed method.

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“…Calculating Human Error Probability (HEP) can be done by HRA techniques [13][14][15][16], while Thermal Hydraulic (TH) simulations using best estimate codes could evaluate the appropriateness of the accident scenarios pre-established by PSA models, identifying and characterizing unknown accident sequences and success criteria [17]. Starting from the International Atomic Energy Agency's (IAEA) structured framework [18] , the combined results of both approaches provide an input on integrated risk-informed decision making to ensure nuclear reactor safety [19][20][21].…”

Section: Accepted Manuscriptmentioning

confidence: 99%