Work

An integrated risk assessment framework for fire accidents on passenger ships

Year: 2025

Type: article

Abstract: Passenger ships offer high capacity and comfort, but fires pose a serious risk of severe casualties. This paper proposes a framework for risk assessment of fire accidents on passenger ships by integrating failure mode and effects analysis (FMEA), risk matrix (RM) and hybrid causal logic (HCL) model. First, based on maritime accident investigation reports, identify the critical risk scenarios that cause fires on passenger ships by applying FMEA and RM. Then, an HCL model is proposed to analyze the risk process of passenger ship fire accidents. The model integrates event sequence diagrams and fault tree analysis to systematically examine the development paths and root causes of passenger ship fires, and quantifies the probabilities of fire progression scenarios. The results show that the highest fire risk stems from a sequence of events: it begins with fuel leakage in the engine room, followed by a failure to promptly address the faulty equipment, which leads to a fire. Due to delayed detection or ineffective fire extinguishing operations, the fire cannot be suppressed and spreads rapidly. Key factors are identified, along with proposed risk control options. The proposed framework can be used for quantitative risk assessment of fire accidents on passenger ships. • Propose an integrated FMEA-RM-HCL framework for fire accidents on passenger ships. • Identify critical risk scenarios using FMEA and risk matrix. • Develop an HCL model and quantitative risk analysis of fire progression scenarios. • Propose targeted risk control options for high-risk fire accident scenarios.

Source: Ocean Engineering

DOI: 10.1016/j.oceaneng.2025.123290

Authors: Shanshan Fu, Zhan Sun, Chailu Jiang, Yunhan Hao, Wengang Mao

Institutions: Chalmers University of Technology, Shanghai Maritime University

Language: English

Topic: Risk and Safety Analysis

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $4,150

Funders: National Natural Science Foundation of China, Trafikverket