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Dynamic safety analysis of process systems using nonlinear and non-sequential accident model

Citation

Adedigba, SA and Khan, FI and Yang, M, Dynamic safety analysis of process systems using nonlinear and non-sequential accident model, Chemical Engineering Research and Design, 111 pp. 169-183. ISSN 0263-8762 (2016) [Refereed Article]

Copyright Statement

2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

DOI: doi:10.1016/j.cherd.2016.04.013

Abstract

Analysis of the safety and reliability of complex engineering systems is becoming challenging and highly demanding. In complex engineering systems, accident causation is a function of nonlinear interactions of several accident contributory factors. Traditional accident models normally use a fault and event trees sequential approach to predict cause-consequence relationships, which unable to capture real interaction thus have limited predictability of accident.This paper presents a new non-sequential barrier-based process accident model. The conditional dependencies among accident contributory factors within prevention barriers are modelled using the Bayesian network with various relaxation strategies, and non-sequential failure of prevention (safety) barriers. The modelling of non-linear interactions in the model led to significant improvement of the predicted probability of an accident when compared with that of sequential technique. This renders valuable information for process safety management. The proposed accident model is tested on a real life case study from the U.S. Chemical Safety Board.

Item Details

Item Type:Refereed Article
Keywords:accident prediction, Bayesian network analysis, leaky noisy-OR gate, non-sequential accident model, sequential accident model, Bayesian networks, chemical analysis, complex networks, reliability analysis, safety engineering, traffic control
Research Division:Engineering
Research Group:Interdisciplinary Engineering
Research Field:Risk Engineering (excl. Earthquake Engineering)
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Khan, FI (Professor Faisal Khan)
ID Code:120384
Year Published:2016
Web of Science® Times Cited:3
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-23
Last Modified:2017-11-06
Downloads:0

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