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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| Veröffentlicht in: | Process safety and environmental protection Jg. 161; S. 571 - 582 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Ramli, Ahmad Fakrul Lim, Jeng Shiun Idris, Ahmad Muzammil Rusli, Risza Nasif, Mohammad Shakir |
| Author_xml | – sequence: 1 givenname: Ahmad Muzammil surname: Idris fullname: Idris, Ahmad Muzammil organization: Department of Chemical Engineering and Centre of Advanced Process Safety (CAPS), Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia – sequence: 2 givenname: Risza surname: Rusli fullname: Rusli, Risza email: risza@utp.edu.my organization: Department of Chemical Engineering and Centre of Advanced Process Safety (CAPS), Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia – sequence: 3 givenname: Mohammad Shakir surname: Nasif fullname: Nasif, Mohammad Shakir organization: Department of Mechanical Engineering and Centre of Advanced Process Safety (CAPS), Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia – sequence: 4 givenname: Ahmad Fakrul surname: Ramli fullname: Ramli, Ahmad Fakrul organization: PETRONAS Research Sdn Bhd, Kawasan Institusi Bangi, Lot 3288 & 3289 Off Jalan Ayer Itam, Kajang 43000, Selangor, Malaysia – sequence: 5 givenname: Jeng Shiun surname: Lim fullname: Lim, Jeng Shiun organization: Process Systems Engineering Centre (PROSPECT), Research Institute for Sustainable Environment (RISE), School of Chemical and Energy Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia |
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| Cites_doi | 10.1016/j.jhazmat.2008.01.111 10.1016/j.jlp.2020.104252 10.1016/j.cjche.2017.10.031 10.1016/j.compchemeng.2012.05.010 10.1021/ie401369v 10.1016/j.jlp.2020.104131 10.1016/j.psep.2016.10.012 10.1016/j.jhazmat.2007.07.123 10.1007/978-1-4419-1153-7_1184 10.1002/prs.12116 10.1016/j.jlp.2005.10.008 10.1057/palgrave.jors.2601758 10.1016/j.jlp.2016.03.004 |
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| Keywords | Gas detectors optimisation Explosion Risk-based Fuzzy multi-objective Computational fluid dynamics |
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| SubjectTerms | Catastrophic events Computational fluid dynamics Computer applications Dynamic models Explosion Explosions Flammability Flammable gases Fuzzy multi-objective Gas detectors Gas detectors optimisation Greedy algorithms Integer programming Linear programming Mathematical models Methodology Mixed integer Multiple objective analysis Natural gas Optimization Placement Risk analysis Risk-based Sensitivity analysis |
| Title | A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities |
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