Dynamic Accident Network Model for Predicting Marine Accidents in Narrow Waterways Under Variable Conditions: A Case Study of the Istanbul Strait DOI Creative Commons
Serdar Yıldız, Özkan Uğurlu, Xinjian Wang

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(12), P. 2305 - 2305

Published: Dec. 14, 2024

Accident analysis models are crucial tools for understanding and preventing accidents in the maritime industry. Despite advances ship technology regulatory frameworks, human factors remain a leading cause of marine accidents. The complexity behavior, influenced by social, technical, psychological aspects, makes accident challenging. Various methods used to analyze accidents, but no single approach is universally chosen use as most effective. Traditional often emphasize errors, technical failures, mechanical breakdowns. However, hybrid models, which combine different approaches, increasingly recognized providing more accurate predictions addressing multiple causal factors. In this study, dynamic model based on Human Factors Analysis Classification System (HFACS) Bayesian Networks proposed predict estimate risks narrow waterways. utilizes past data expert judgment assess potential ships encounter when navigating these confined areas. Uniquely, enables prediction probabilities under varying operational conditions, offering practical applications such real-time risk estimation vessels before entering Istanbul Strait. By insights, supports traffic operators implementing preventive measures enter high-risk zones. results study can serve decision-support system not only VTS operators, shipmasters, company representatives also national international stakeholders industry, aiding both probability development measures.

Language: Английский

Risk influencing factors on the consequence of waterborne transportation accidents in China (2013-2023) based on data-driven machine learning DOI
Weiliang Qiao,

Enze Huang,

Meng Zhang

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 110829 - 110829

Published: Jan. 1, 2025

Language: Английский

Citations

2
Integration of MIMAH and Fuzzy Bayesian Networks for risk analysis in chemical tanker loading operations DOI
Cenk Ay

Journal of Marine Engineering & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: Feb. 13, 2025

This study provides a systematic risk assessment approach for chemical tanker loading operations, focusing on high-risk scenario identified through operational data from model vessel. To address the complexities of transportation, hybrid methodology combining Methodology Identification Major Accident Hazards (MIMAH) and Fuzzy Bayesian Network (FBN) analysis was developed. MIMAH's structured framework systematically identifies critical events using Bow-Tie (BT) diagram, integrating Fault Tree (FT) Event (ET) providing thorough breakdown potential accident pathways. BT structure converted into (BN) to improve probability estimations by incorporating conditional dependencies expert-driven fuzzy logic, particularly where historical limited. The further employed dual-method sensitivity analysis, Fussell-Vesely (FV) importance measures Improvement Index (II), identify improvement-prone basic (BEs). Key findings highlight dominance human error in events, manifold connection failures incorrect valve alongside mechanical vulnerabilities with significant improvement potential. extends ARAMIS principles maritime contexts, reliability-based fuzzy-based estimation methods detailed adaptable that enhances safety resilience hazardous transport.

Language: Английский

Citations

1
Creating an Incident Investigation Framework for a Complex Socio-Technical System: Application of Multi-label Text Classification and Bayesian Network Structure Learning DOI

Mohammadreza Karimi Dehkori,

Fereshteh Sattari, Lianne Lefsrud

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 110971 - 110971

Published: Feb. 1, 2025

Language: Английский

Citations

1
Prevention and control strategy of coal mine water inrush accident based on case-driven and Bow-Tie-Bayesian model DOI

Xin Tong,

Xuezhao Zheng, Yongfei Jin

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135312 - 135312

Published: Feb. 1, 2025

Language: Английский

Citations

0
A Literature Review: Enhancing Maritime Risk Assessment through Advanced Fuzzy Approach DOI Open Access

Diyah Purwitasari,

Ketut Buda Artana, Dhimas Widhi Handani

et al.

IOP Conference Series Earth and Environmental Science, Journal Year: 2025, Volume and Issue: 1461(1), P. 012033 - 012033

Published: March 1, 2025

Abstract Maritime transportation played a vital role in global trade and economic growth but faced risks from weather, human error, equipment failures. Traditional risk assessment methods often fell short addressing the complexities uncertainties of maritime operations, highlighting need for more effective approaches. This review examined application Fuzzy Bayesian Networks (FBN) assessment, focusing on its integration with fuzzy logic probabilistic tools to improve safety. Findings indicated that combining frequency consequence analysis provided flexible accurate way assess risks, helping predict prevent accidents by deepening insights into likelihood impact events. integrated model facilitated tailored mitigation strategies, promoting safer resilient operations. As industry expanded, incorporating advanced became essential enhancing safety decision-making. The evolving potential FBN, particularly big data machine learning, underscored fostering efficient, sustainable practices. Future research was encouraged refine these models apply them new technologies management, aligning Sustainable Development Goals enhance resilience sustainability sector.

Language: Английский

Citations

0
Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries DOI Creative Commons
Andres Laasma, Deniece Aiken, Kadi Kasepõld

et al.

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(4), P. 688 - 688

Published: March 28, 2025

As the focus on climate action and sustainable development of shipping industry intensifies, maritime sector has intensified its decarbonization. Although ferry accounts for a small part global fleet, it plays crucial role in specific regions. This study examines data from an energy monitoring system installed double-ended Estonian over period 2022 to 2024. The empirical results clearly show that targeted adjustments can lead substantial fuel consumption reductions as optimal operation vessel requires equal power aft fore engines particularly when operating under cold or icy conditions. Additionally, research finds real-time together with integrating environmental factors supports efficiency fulfilling regulatory requirements. analysis reveals corrections balanced decision-making generate savings extended emission reductions. suggested framework offers operators practical economical ways meeting sustainability

Language: Английский

Citations

0
Data-Driven Analysis of the Causal Chain of Waterborne Traffic Accidents: A Hybrid Framework Based on an Improved Human Factors Analysis and Classification System with a Bayesian Network DOI Creative Commons
Xiangyu Yin, Yan Yan, Jiahao Wang

et al.

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(3), P. 393 - 393

Published: Feb. 20, 2025

In the context of economic globalization, waterborne transportation plays an important role in international trade and logistics. However, traffic accidents pose a severe threat to life, property safety, environment. To gain deeper understanding causal mechanisms behind accidents, we conducted data-driven analysis chain accidents. By constructing hybrid framework integrating improved HFACS (Human Factors Analysis Classification System) with Bayesian network model, multi-dimensional accident causes. The constructed model was quantitatively analyzed by applying genie software samples collected from China MSA. results indicate that there are 12, 3, 6, 2, 4, 7 chains leading collisions, contact, fires/explosions, windstorm sinking, other types respectively. These research can serve as reference for enhancement safety transportation.

Language: Английский

Citations

0
Research on Response Strategies for Inland Waterway Vessel Traffic Risk Based on Cost-Effect Trade-Offs DOI Creative Commons
Yanyi Chen,

Ziyang Ye,

Tao Wang

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(9), P. 1659 - 1659

Published: Sept. 16, 2024

Compared to maritime vessel traffic accidents, there is a scarcity of available, and only incomplete, accident data for inland waterway accidents. Additionally, the characteristics different segments vary significantly, factors affecting navigation safety risks their mechanisms may also differ. Meanwhile, in recent years, extreme weather events have been frequent waterways, has clear trend towards larger vessels, bringing about new hazards management challenges. Currently, research on mainly focuses risk assessment, with scarce quantitative studies mitigation measures. This paper proposes method improving safety, based cost-effectiveness trade-off approach mitigate The links effectiveness cost measures constructs comprehensive cost-benefit evaluation model using fuzzy Bayesian quantification conversion techniques, considering reduction effects under uncertain conditions various costs they incur. Taking upper, middle, lower reaches Yangtze River as examples, this evaluates key provides most cost-effective strategies. Findings reveal that, even if waterways share same sources, due environmental differences. Moreover, no inherent correlation between best-performing terms benefits lowest-cost measures, nor are necessarily recommended. proposed case provide theoretical support scientifically formulating complex environments offer guidance departments determine future work directions.

Language: Английский

Citations

0
Dynamic Accident Network Model for Predicting Marine Accidents in Narrow Waterways Under Variable Conditions: A Case Study of the Istanbul Strait DOI Creative Commons
Serdar Yıldız, Özkan Uğurlu, Xinjian Wang

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(12), P. 2305 - 2305

Published: Dec. 14, 2024

Accident analysis models are crucial tools for understanding and preventing accidents in the maritime industry. Despite advances ship technology regulatory frameworks, human factors remain a leading cause of marine accidents. The complexity behavior, influenced by social, technical, psychological aspects, makes accident challenging. Various methods used to analyze accidents, but no single approach is universally chosen use as most effective. Traditional often emphasize errors, technical failures, mechanical breakdowns. However, hybrid models, which combine different approaches, increasingly recognized providing more accurate predictions addressing multiple causal factors. In this study, dynamic model based on Human Factors Analysis Classification System (HFACS) Bayesian Networks proposed predict estimate risks narrow waterways. utilizes past data expert judgment assess potential ships encounter when navigating these confined areas. Uniquely, enables prediction probabilities under varying operational conditions, offering practical applications such real-time risk estimation vessels before entering Istanbul Strait. By insights, supports traffic operators implementing preventive measures enter high-risk zones. results study can serve decision-support system not only VTS operators, shipmasters, company representatives also national international stakeholders industry, aiding both probability development measures.

Language: Английский

Citations

0