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Hazard identification for innovative LNG regasification technologies

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  • Paltrinieri, Nicola
  • Tugnoli, Alessandro
  • Cozzani, Valerio

Abstract

Emerging risks may arise from process intensification and new scenarios due to the innovative technologies and higher potentialities of new LNG regasification facilities. In the conventional hazard identification process it is difficult to include new scenarios related to innovative technologies or facilities, for which limited or no operational experience is available. In the present study, a new technique for HAZard IDentification (HAZID), named Dynamic Procedure for Atypical Scenarios Identification (DyPASI), was applied to identify atypical accident scenarios in LNG terminals. The technique aims to make easier and more systematic the process of learning from early warnings and identify atypical accident scenarios otherwise disregarded by common HAZID techniques. The comparison with a survey of the accident scenarios typically considered in available Environmental Impact Assessment (EIA) studies evidences that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards in particular for new or innovative technologies, where limited operational experience is available.

Suggested Citation

  • Paltrinieri, Nicola & Tugnoli, Alessandro & Cozzani, Valerio, 2015. "Hazard identification for innovative LNG regasification technologies," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 18-28.
    • Handle: RePEc:eee:reensy:v:137:y:2015:i:c:p:18-28
    DOI: 10.1016/j.ress.2014.12.006
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    References listed on IDEAS

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    1. Makridakis, Spyros & Taleb, Nassim, 2009. "Decision making and planning under low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 716-733, October.
    2. Tugnoli, Alessandro & Cozzani, Valerio & Di Padova, Annamaria & Barbaresi, Tiziana & Tallone, Fabrizio, 2012. "Mitigation of fire damage and escalation by fireproofing: A risk-based strategy," Reliability Engineering and System Safety, Elsevier, vol. 105(C), pages 25-35.
    3. Paltrinieri, Nicola & Øien, Knut & Cozzani, Valerio, 2012. "Assessment and comparison of two early warning indicator methods in the perspective of prevention of atypical accident scenarios," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 21-31.
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    Cited by:

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    2. Maroua Ghram & Hela Moalla Frikha, 2022. "Multiple Hierarchically Structured Criteria in ARAS Method Under Fuzzy Environment," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 11(1), pages 1-19, January.
    3. Martin Folch-Calvo & Francisco Brocal-Fernández & Cristina González-Gaya & Miguel A. Sebastián, 2020. "Analysis and Characterization of Risk Methodologies Applied to Industrial Parks," Sustainability, MDPI, vol. 12(18), pages 1-35, September.
    4. Hu, Jinqiu & Khan, Faisal & Zhang, Laibin, 2021. "Dynamic resilience assessment of the Marine LNG offloading system," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    5. Noguchi, H. & Hienuki, S. & Fuse, M., 2020. "Network theory-based accident scenario analysis for hazardous material transport: A case study of liquefied petroleum gas transport in japan," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. Zbigniew Rogala & Arkadiusz Brenk & Ziemowit Malecha, 2019. "Theoretical and Numerical Analysis of Freezing Risk During LNG Evaporation Process," Energies, MDPI, vol. 12(8), pages 1-19, April.
    7. Pospíšil, Jiří & Charvát, Pavel & Arsenyeva, Olga & Klimeš, Lubomír & Špiláček, Michal & Klemeš, Jiří Jaromír, 2019. "Energy demand of liquefaction and regasification of natural gas and the potential of LNG for operative thermal energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 1-15.

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