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Robust multi-objective optimization of safety barriers performance parameters for NaTech scenarios risk assessment and management

Author

Listed:
  • Francesco Di Maio

    (POLIMI - Politecnico di Milano [Milan])

  • Stefano Marchetti

    (POLIMI - Politecnico di Milano [Milan])

  • Enrico Zio

    (POLIMI - Politecnico di Milano [Milan], CRC - Centre de recherche sur les Risques et les Crises - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres)

Abstract

Safety barriers are to be designed to bring the largest benefit in terms of accidental scenarios consequences mitigation at the most reasonable cost. In this paper, we formulate the problem of the identification of the optimal performance parameters of the barriers that can at the same time allow for the consequences mitigation of Natural Technological (NaTech) accidental scenarios at reasonable cost as a Multi-Objective Optimization (MOO) problem. The MOO is solved for a case study of literature, consisting in a chemical facility composed by three tanks filled with flammable substances and equipped with six safety barriers (active, passive and procedural), exposed to NaTech scenarios triggered by either severe floods or earthquakes. The performance of the barriers is evaluated by a phenomenological dynamic model that mimics the realistic response of the system. The uncertainty of the relevant parameters of the model (i.e., the response time of active and procedural barriers and the effectiveness of the barriers) is accounted for in the optimization, to provide robust solutions. Results for this case study suggest that the NaTech risk is optimally managed by improving the performances of four-out-of-six barriers (three active and one passive). Practical guidelines are provided to retrofit the safety barriers design.

Suggested Citation

  • Francesco Di Maio & Stefano Marchetti & Enrico Zio, 2023. "Robust multi-objective optimization of safety barriers performance parameters for NaTech scenarios risk assessment and management," Post-Print hal-04103505, HAL.
    • Handle: RePEc:hal:journl:hal-04103505
    DOI: 10.1016/j.ress.2023.109245
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    Cited by:

    1. Cai, Jitao & Wu, Jiansong & Yuan, Shuaiqi & Reniers, Genserik & Bai, Yiping, 2024. "Risk-based optimization of emergency response systems for accidental gas leakage in utility tunnels," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Dui, Hongyan & Lu, Yaohui & Chen, Liwei, 2024. "Importance-based system cost management and failure risk analysis for different phases in life cycle," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    3. Cheraghi, Morteza & Taghipour, Sharareh, 2024. "A mathematical optimization model for determining safety integrity levels in process facilities," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Khakzad, Nima, 2023. "A goal programming approach to multi-objective optimization of firefighting strategies in the event of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    5. Men, Jinkun & Chen, Guohua & Reniers, Genserik, 2024. "Pareto-based design optimization of chemical tank farm using a trade-off between domino effects related and land resource utilization efficiency," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

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