An integrated system theoretic accident model and process (STAMP)-Bayesian network (BN) for safety analysis of water mist system on tanker ships

Bulut Ozan Ceylan · Şükrü İlke Sezer · Emre Akyüz

16 citations0/0 files storedApplied Ocean Research

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Risk and Safety Analysis Maritime Navigation and Safety Marine and Coastal Research

Abstract

• A failure analysis of water mist system on tanker ships is presented. • Failure analysis is conducted using an STAMP and process and BN. • The outputs provide knowledge to understand water mist system failure. A water mist on tanker ships is a specialized fire suppression system intended to mitigate fire hazards on board. This innovative safety measure disperses microscopic water droplets, creating a mist that rapidly absorbs heat and suppresses fires by reducing oxygen levels and cooling the surrounding area autonomously. This paper attempts to perform a comprehensive safety analysis of the water mist system on a tanker ship under the system theoretic accident model and process (STAMP) and Bayesian network (BN) robust modeling, which is capable of presenting a dynamic structure comprising complex elements. In the paper, whilst the STAMP is utilized to determine failure scenarios by establishing a hierarchical control and feedback model structure, the BN quantifies the probabilities of potential failures based on the outcomes of STAMP. A water mist system in tanker ships is analyzed under STAMP-BN modeling since it is an essential part of the ship, including an advanced system comprising elements of human, software, and hardware. The research results indicate that the failure probability of the water mist system has a failure probability of 3.93E-02. Besides its robust theoretical background, the research findings will provide a helpful reference for maritime safety managers, safety inspectors, technical inspectors, HSEQ managers, and ship crew on improving fire-fighting safety in tanker ships.

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References

2012Engineering a Safer World 2018Safety analysis of process systems using Fuzzy Bayesian Network (FBN)2019What do applications of systems thinking accident analysis methods tell us about accident causation? A systematic review of applications between 1990 and 2018 2020Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network 2012Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations 2020Application of fuzzy bow-tie risk analysis to maritime transportation: The case of ship collision during the STS operation 2020An FMEA-based TOPSIS approach under single valued neutrosophic sets for maritime risk evaluation: the case of ship navigation safety 2021Quantitative failure analysis for static electricity-related explosion and fire accidents on tanker vessels under fuzzy bow-tie CREAM approach

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2025Risk propagation analysis of domino effect in chemical accident: An integrated approach with data mining and Bayesian networks 2025Probabilistic risk assessment for inert gas system on oil tanker ships using system theoretic accident model and process (STAMP) and Bayesian belief network (BBN)

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