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Göksu, B, Şakar, C and Yüksel, O (2024) A probabilistic assessment of ship blackout incident with Fault Tree Analysis into (FTA) Bayesian Network (BN). Journal of Marine Engineering & Technology. pp. 1-16. ISSN 2046-4177
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A probabilistic assessment of ship blackout incident with Fault Tree Analysis into (FTA) Bayesian Network (BN).pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
Blackouts in maritime activities can cause propulsion loss and dangerous maritime conditions. Bayesian risk analysis is applied to ship blackout incidents in this study to improve understanding and reduce risks. Using Fault Tree Analysis (FTA), a Bayesian Network (BN) model incorporates fuel quality, lubricating oil quality, sensor error, injector error, and mechanical defects to estimate blackout probability. The model analyses how hazards and their interactions affect this situation using probabilistic inference. Sensitivity analysis identifies variables that affect blackout probabilities and prioritises risk mitigation solutions. Based on prior and posterior probabilities, ‘Automatic Voltage Regulator Failure’ (0.03 prior, 0.17 posterior), ‘Rotor Mechanical Fault’ (0.03 prior, 0.15 posterior), and ‘High Cooling Water Temperature’ (0.03 prior, 0.13 posterior) are the top three blackout causes. Other significant variables include ‘Switchboard Line Failure,’ ‘Faulty Fuel Pump,’ ‘Rotor Open Circuit,’ and ‘Temperature Sensor Failure’ in relative amounts. Bayesian risk analysis can identify and minimise marine blackout concerns, giving decision-makers a comprehensive framework for informed decision-making and proactive risk management. This research emphasises blackout accidents’ importance, improving maritime transportation safety and reliability.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TC Hydraulic engineering. Ocean engineering V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering |
| Divisions: | Engineering |
| Publisher: | Taylor and Francis Group |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 13 Nov 2024 12:59 |
| Last Modified: | 13 Nov 2024 13:00 |
| DOI or ID number: | 10.1080/20464177.2024.2423425 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/24761 |
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