Title: Coupling of risk factors in emergency processes for oil storage system fires based on the Bayesian network and N-K model

Authors: Changfeng Yuan; Xing Sun; Lulu Niu; Yating Tong; Qing Zhang

Addresses: School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning Province, China ' School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning Province, China ' School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning Province, China ' School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning Province, China ' School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning Province, China

Abstract: Frequent secondary accidents caused by emergency treatment of Oil Storage System Fires (OSSF) show that risk factors and their interactions in emergency processes can lead to recurrence of accidents. To quantitatively evaluate coupling effects of risk factors on accident development, a novel Risk Coupling Effect Analysis (RCEA) method based on the Bayesian Network (BN) and N-K model is proposed. Based on a statistical analysis of 252 typical accidents, risk coupling types caused by different factors are defined. Risk coupling value is calculated using the N-K model. A RCAE model based on the BN and N-K model is constructed. The model is used to analyse the coupling effect of risk factors, including: coupling degree variation characteristics, sensitivity and joint adjustment measures of risk factors. Some risk management suggestions are proposed. This study presents a new research idea and measurement method for evaluating risk coupling effect in emergency processes for OSSF.

Keywords: oil storage system fire; risk factor; Bayesian network; N-K model; coupling effect.

DOI: 10.1504/IJRS.2026.150484

International Journal of Reliability and Safety, 2026 Vol.20 No.1, pp.36 - 70

Received: 29 May 2024
Accepted: 15 Jan 2025
Published online: 15 Dec 2025 *

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