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A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities

A flammable gas detection system is one of the critical control strategies of catastrophic events such as fire and explosion. While gas detector technology has improved significantly, adopting a methodology for optimal placement of gas detectors is still an issue, especially when integrated with a r...

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Main Authors: Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.
Format: Article
Published: Institution of Chemical Engineers 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127211491&doi=10.1016%2fj.psep.2022.03.001&partnerID=40&md5=44fde599568ca592504ac7707015e18b
http://eprints.utp.edu.my/33120/
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spelling my.utp.eprints.331202022-07-06T07:55:53Z A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities Idris, A.M. Rusli, R. Nasif, M.S. Ramli, A.F. Lim, J.S. A flammable gas detection system is one of the critical control strategies of catastrophic events such as fire and explosion. While gas detector technology has improved significantly, adopting a methodology for optimal placement of gas detectors is still an issue, especially when integrated with a risk-based approach. An enhancement of a risk-based approach is proposed to optimise the placement of flammable gas detectors by integrating a formulation of fuzzy multi-objective mixed-integer linear programming with the goal of minimising the residual risk and total number of detectors for effective explosion protection. The proposed methodology primarily begins with the identification of critical leak scenarios that require detection followed by the prediction of a targeted gas cloud and dispersion analysis using a computational fluid dynamic model. Risk analysis is conducted to identify high risk areas that need flammable gas detectors protection, which is the input for the mathematical model. The proposed risk-based model was tested using a case study involving a natural gas liquids (NGL) recovery unit, and the results were compared to a published greedy algorithm (GA) formulation. By using mixed-integer linear programming (MILP) formulation, the number of detectors needed are lower with higher risk reductions compared to the GA formulation. Additionally, a sensitivity analysis was performed to determine the proposed model's response to parameter variations. © 2022 The Institution of Chemical Engineers Institution of Chemical Engineers 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127211491&doi=10.1016%2fj.psep.2022.03.001&partnerID=40&md5=44fde599568ca592504ac7707015e18b Idris, A.M. and Rusli, R. and Nasif, M.S. and Ramli, A.F. and Lim, J.S. (2022) A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities. Process Safety and Environmental Protection, 161 . pp. 571-582. http://eprints.utp.edu.my/33120/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description A flammable gas detection system is one of the critical control strategies of catastrophic events such as fire and explosion. While gas detector technology has improved significantly, adopting a methodology for optimal placement of gas detectors is still an issue, especially when integrated with a risk-based approach. An enhancement of a risk-based approach is proposed to optimise the placement of flammable gas detectors by integrating a formulation of fuzzy multi-objective mixed-integer linear programming with the goal of minimising the residual risk and total number of detectors for effective explosion protection. The proposed methodology primarily begins with the identification of critical leak scenarios that require detection followed by the prediction of a targeted gas cloud and dispersion analysis using a computational fluid dynamic model. Risk analysis is conducted to identify high risk areas that need flammable gas detectors protection, which is the input for the mathematical model. The proposed risk-based model was tested using a case study involving a natural gas liquids (NGL) recovery unit, and the results were compared to a published greedy algorithm (GA) formulation. By using mixed-integer linear programming (MILP) formulation, the number of detectors needed are lower with higher risk reductions compared to the GA formulation. Additionally, a sensitivity analysis was performed to determine the proposed model's response to parameter variations. © 2022 The Institution of Chemical Engineers
format Article
author Idris, A.M.
Rusli, R.
Nasif, M.S.
Ramli, A.F.
Lim, J.S.
spellingShingle Idris, A.M.
Rusli, R.
Nasif, M.S.
Ramli, A.F.
Lim, J.S.
A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
author_facet Idris, A.M.
Rusli, R.
Nasif, M.S.
Ramli, A.F.
Lim, J.S.
author_sort Idris, A.M.
title A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
title_short A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
title_full A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
title_fullStr A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
title_full_unstemmed A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
title_sort fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities
publisher Institution of Chemical Engineers
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127211491&doi=10.1016%2fj.psep.2022.03.001&partnerID=40&md5=44fde599568ca592504ac7707015e18b
http://eprints.utp.edu.my/33120/
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score 13.211869

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