Evidential Analytic Hierarchy Process Dependence Assessment Methodology in Human Reliability Analysis

Luyuan Chen; Xinyi Zhou; Fuyuan Xiao; Yong Deng; Sankaran Mahadevan

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자료유형: 학술저널

저자정보: Luyuan Chen Xinyi Zhou Fuyuan Xiao Yong Deng Sankaran Mahadevan

저널정보: 한국원자력학회 Nuclear Engineering and Technology Nuclear Engineering and Technology 제49권 제1호

발행연도: 2017.1

수록면: 113 - 123 (11page)

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In human reliability analysis, dependence assessment is an important issue in risky largecomplex systems, such as operation of a nuclear power plant. Many existing methodsdepend on an expert's judgment, which contributes to the subjectivity and restrictions ofresults. Recently, a computational method, based on the DempstereShafer evidence theoryand analytic hierarchy process, has been proposed to handle the dependence in humanreliability analysis. The model can deal with uncertainty in an analyst's judgment andreduce the subjectivity in the evaluation process. However, the computation is heavy andcomplicated to some degree. The most important issue is that the existing method is in apositive aspect, which may cause an underestimation of the risk. In this study, a newevidential analytic hierarchy process dependence assessment methodology, based on theimprovement of existing methods, has been proposed, which is expected to be easier andmore effective.

#Analytic Hierarchy Process #Dempstere-Shafer Evidence Theory #Dependence Assessment #Human Reliability Analysis #Nuclear Power Plant

참고문헌 (24)

참고문헌 신청

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B. Kirwan / 1996 / The validation of three human reliability quantification techniquesdTHERP, HEART and JHEDI: Part 1dtechnique descriptions and validation issues / Appl. Er

B. Reer / 2008 / Review of advances in human reliability analysis of errors of commission, part 1: EOC identification / Reliab. Eng. Syst. Saf 93 : 1091 ~ 1104

Chung-Kung Lo / 2014 / Treating Uncertainties in a Nuclear Seismic Probabilistic Risk Assessment by Means of the Dempster-Shafer Theory of Evidence / Nuclear Engineering and

E. Pate-Cornell / 2012 / On black swans and perfect storms: risk analysis and management when statistics are not enough / Risk Anal 32 : 1823 ~ 1833

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