Human reliability analysis of the Tokai-Mura accident through a THERP-CREAM and expert opinion auditing approach

被引:23
作者
Ribeiro, A. C. [1 ]
Sousa, A. L. [2 ]
Duarte, J. P. [3 ]
Frutuoso e Melo, P. F. [4 ]
机构
[1] Bayer Crop Sci Brasil SA, Estr Boa Esperanca 650, BR-26110100 Belford Roxo, RJ, Brazil
[2] Natl Commiss Nucl Energy CNEN, Rua Gen Severiano 90, BR-22290901 Rio De Janeiro, RJ, Brazil
[3] Univ Sao Paulo, Polytech Sch, Dept Telecommun & Control Engn, Ave Prof Luciano Gualberto,Travessa 3,158, BR-05508900 Sao Paulo, SP, Brazil
[4] Univ Fed Rio de Janeiro, COPPE, Grad Program Nucl Engn, Ave Horacio Macedo 2030,Bloco G,Sala 206, BR-21941914 Rio De Janeiro, RJ, Brazil
关键词
Tokai-Mura accident; Human reliability analysis; THERP; CREAM; Expert opinion elicitation;
D O I
10.1016/j.ssci.2016.04.009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a human reliability analysis (HRA) model that allows the incorporation of features related to facility conditions to determine human error probabilities (HEP) used in probabilistic safety analyses of process plants. We present an approach to show the predominance of human factors as an accident cause, as well as existing methodologies for HEP determination and their deficiencies in incorporating socio-technical elements that influence them. Such elements are: inappropriate design, training, procedures, communication, safety culture, management in the production process changes, emergency planning, accident investigation, environmental factors, maintenance workload and human-system interface. A mathematical model is proposed to incorporate these elements taking into account their contribution weights as well as measuring their degree of implementation in the plant. This creates a factor that can modify existing HEPs, giving values that better reflect plant reality. The model was applied to the accident that occurred in 1999 in Tokai-Mura, Japan. The modified HEP was 2 times greater than the nominal HEP. This shows that considering organizational factors thoroughly allows for a more realistic plant behavior modeling in face of abnormal events. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:269 / 279
页数:11
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