Predictive risk analysis for leakage accidents with dynamic behaviour

Kong, X, Huang, R, Li, H ORCID: 0000-0001-6429-9097, Kang, J ORCID: 0000-0002-8975-5025, Dong, Y ORCID: 0000-0002-7242-5388, Guedes Soares, C ORCID: 0000-0002-8570-4263 and Wang, J ORCID: 0000-0003-4646-9106 (2026) Predictive risk analysis for leakage accidents with dynamic behaviour. Reliability Engineering and System Safety, 271. ISSN 0951-8320 (Accepted)

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Abstract

A predictive risk analysis approach is proposed for modelling leakage accidents with dynamic behaviour based on time-series simulations in order to enhance data foundation of risk analysis tasks. Critical failure items are first identified by the Failure Mode and Effects Analysis model and the occurrence probabilities of which are subsequently computed by the Bayesian and Event Tree Analysis methods. The dynamic behaviour of the accidents is simulated to reveal their time-series failure consequences. With the probabilities and consequences obtained, a predictive risk analysis approach is established as a basis to calculate the risk index of accidents with the consideration of dynamic behaviours. The applicability and superior performance of the proposed approach are illustrated by a leakage risk analysis of offshore hydrogen storage systems. Overall, the proposed approach extends the existing inductive risk analysis concepts to predictive patterns and contributes to leakage accidents analysis and prevention with the situation of data and knowledge scarcities.

Item Type:	Article
Uncontrolled Keywords:	Offshore hydrogen storage system; Failure mode and effect analysis; Bayesian theory; Long short-term memory; Dynamic failure behaviour; 40 Engineering; 4010 Engineering Practice and Education; 3 Good Health and Well Being; 01 Mathematical Sciences; 09 Engineering; 15 Commerce, Management, Tourism and Services; Strategic, Defence & Security Studies; 35 Commerce, management, tourism and services; 40 Engineering; 49 Mathematical sciences
Subjects:	T Technology > T Technology (General) T Technology > TD Environmental technology. Sanitary engineering
Divisions:	Engineering
Publisher:	Elsevier
Date of acceptance:	13 January 2026
Date of first compliant Open Access:	29 April 2026
Date Deposited:	28 Apr 2026 10:14
Last Modified:	29 Apr 2026 00:50
DOI or ID number:	10.1016/j.ress.2026.112238
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28461

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