A skill-enhanced retrieval-augmented generation expert system framework for offshore accident analysis: Combining fuzzy inference, Dempster-Shafer evidential reasoning, and expert-gated skill adaptation

Ren, J ORCID: 0000-0003-4640-824X (2026) A skill-enhanced retrieval-augmented generation expert system framework for offshore accident analysis: Combining fuzzy inference, Dempster-Shafer evidential reasoning, and expert-gated skill adaptation. Ocean Engineering, 364. ISSN 0029-8018

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Abstract

Traditional rule-based expert systems for offshore safety assessment suffer from labour-intensive knowledge acquisition and an inability to evolve with operational experience. This paper presents a Skill-Enhanced Retrieval-Augmented Generation (RAG) Expert System Framework in which the “Skill” is a versioned, self- contained module encoding domain-specific fuzzy inference templates with expert-gated weight updates. Applied to FPSO–shuttle tanker collision risk during tandem offloading, the framework compresses 245 IF–THEN rules into 12 weighted templates across five Skills, achieving Pearson r = 0.987 and F1 = 0.944 for high-risk classification. One feedback cycle confirmed that the version-control and weight-update mechanism operates as intended, with five of six proposed adjustments, ranging up to 4.7%, approved and committed by the expert panel. This result is not a claim of superior risk-assessment accuracy relative to the established baseline. It is evidence that the knowledge-engineering architecture, grounded in maintainability, modularity, and traceability, can be put into practice and audited at every step. The contribution is architectural, not computational. The framework is positioned as a feasibility-oriented knowledge-engineering contribution: it demonstrates that Skill-structured RAG can support maintainable, modular, and traceable offshore safety knowledge bases, not that it outperforms established expert-assessment methods on general offshore risk problems.

Item Type:	Article
Uncontrolled Keywords:	0405 Oceanography; 0905 Civil Engineering; 0911 Maritime Engineering; Civil Engineering; 4005 Civil engineering; 4012 Fluid mechanics and thermal engineering; 4015 Maritime engineering
Subjects:	T Technology > TC Hydraulic engineering. Ocean engineering
Divisions:	Engineering
Publisher:	Elsevier
Date of acceptance:	4 July 2026
Date of first compliant Open Access:	10 July 2026
Date Deposited:	10 Jul 2026 09:29
Last Modified:	10 Jul 2026 09:29
DOI or ID number:	10.1016/j.oceaneng.2026.126908
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28989

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