A quantitative LNG risk assessment model based on integrated Bayesian-Catastrophe-EPE method. (May 2021)
- Record Type:
- Journal Article
- Title:
- A quantitative LNG risk assessment model based on integrated Bayesian-Catastrophe-EPE method. (May 2021)
- Main Title:
- A quantitative LNG risk assessment model based on integrated Bayesian-Catastrophe-EPE method
- Authors:
- Wu, Jiansong
Bai, Yiping
Zhao, Huanhuan
Hu, Xiaofeng
Cozzani, Valerio - Abstract:
- Highlights: A Bayesian-Catastrophe-EPE model for LNG risk assessment is proposed. The BCEPE model can objectively quantify the causal relationship of LNG risks. Roll over and misoperation are identified as the critical hazards of LNG leakage. Risk (hazard) correlations are quantified to provide technical supports for effectively controlling risks. Abstract: Increasing quantities of natural gas are transported as liquefied natural gas (LNG) worldwide, and LNG is also proposed for use as a clean fuel for ships and trucks. This scenario raises concerns for the safety of LNG bunkering and storage at ports, due to the potentially severe accidents that may arise from LNG leakage. In this paper, an integrated quantitative risk assessment model for LNG bunkering and storage at ports based on Bayesian-Catastrophe-EPE (Energy transfer theory, Preliminary hazard analysis and Evolution tree) method was proposed. The energy-based EPE model was used to derive Bayesian network (BN) causal structure, and the catastrophe theory was employed to deal with experts' judgment to determine the conditional probability tables of BN. The proposed BN-based risk assessment model can provide a novel perspective to identify hazards and risks, and to assess the evolution process of LNG accidents from causes to consequences. The results of scenario analysis of typical LNG accidents demonstrate the soundness and applicability of the proposed model. Moreover, sensitivity analysis was implemented to identifyHighlights: A Bayesian-Catastrophe-EPE model for LNG risk assessment is proposed. The BCEPE model can objectively quantify the causal relationship of LNG risks. Roll over and misoperation are identified as the critical hazards of LNG leakage. Risk (hazard) correlations are quantified to provide technical supports for effectively controlling risks. Abstract: Increasing quantities of natural gas are transported as liquefied natural gas (LNG) worldwide, and LNG is also proposed for use as a clean fuel for ships and trucks. This scenario raises concerns for the safety of LNG bunkering and storage at ports, due to the potentially severe accidents that may arise from LNG leakage. In this paper, an integrated quantitative risk assessment model for LNG bunkering and storage at ports based on Bayesian-Catastrophe-EPE (Energy transfer theory, Preliminary hazard analysis and Evolution tree) method was proposed. The energy-based EPE model was used to derive Bayesian network (BN) causal structure, and the catastrophe theory was employed to deal with experts' judgment to determine the conditional probability tables of BN. The proposed BN-based risk assessment model can provide a novel perspective to identify hazards and risks, and to assess the evolution process of LNG accidents from causes to consequences. The results of scenario analysis of typical LNG accidents demonstrate the soundness and applicability of the proposed model. Moreover, sensitivity analysis was implemented to identify critical hazards and quantify the correlations between each element considered in LNG accidents. The proposed risk assessment framework is of great significance to widen the technical tools available to support safety assessment and loss prevention of LNG bunkering and storage at ports. … (more)
- Is Part Of:
- Safety science. Volume 137(2021)
- Journal:
- Safety science
- Issue:
- Volume 137(2021)
- Issue Display:
- Volume 137, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 137
- Issue:
- 2021
- Issue Sort Value:
- 2021-0137-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05
- Subjects:
- LNG -- Risk assessment -- Bayesian network -- Catastrophe theory -- Critical hazards
Industrial accidents -- Periodicals
Accident Prevention -- Periodicals
Safety -- Periodicals
Travail -- Accidents -- Périodiques
363.11 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09257535 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/safety-science/ ↗ - DOI:
- 10.1016/j.ssci.2021.105184 ↗
- Languages:
- English
- ISSNs:
- 0925-7535
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8069.124900
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 24990.xml