Functional resonance analysis via a genetic algorithm to ensure cost-effective maintenance planning DOI Creative Commons
Riccardo Patriarca, Lorenzo Lovaglio, Francesco Simone

et al.

International Journal of Production Economics, Journal Year: 2025, Volume and Issue: unknown, P. 109516 - 109516

Published: Jan. 1, 2025

Language: Английский

Analysis of factors affecting the severity of marine accidents using a data-driven Bayesian network DOI
Yuhao Cao, Xinjian Wang, Yihang Wang

et al.

Ocean Engineering, Journal Year: 2023, Volume and Issue: 269, P. 113563 - 113563

Published: Jan. 3, 2023

Language: Английский

Citations

98
Risk evolution and prevention and control strategies of maritime accidents in China's coastal areas based on complex network models DOI
Jian Deng, Shaoyong Liu, Yaqing Shu

et al.

Ocean & Coastal Management, Journal Year: 2023, Volume and Issue: 237, P. 106527 - 106527

Published: Feb. 17, 2023

Language: Английский

Citations

55
A data-driven risk model for maritime casualty analysis: A global perspective DOI Creative Commons
Kaiwen Zhou, Wenbin Xing, Jingbo Wang

et al.

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 244, P. 109925 - 109925

Published: Dec. 30, 2023

Maritime casualty analysis needs to be addressed given the increasing safety demand in field due accidents' low-frequency and high-consequence features. This paper aims delve deeper into factors that affect maritime accident casualties by establishing a new database conducting an evolution analysis. Based on refined dataset, pure data-driven Bayesian network (BN) model is developed conduct of accidents occurred under different ship operational conditions. Methodologically, it introduces risk improve accuracy through enriched updated database. Furthermore, categorised five datasets based temporal development trends better analyse casualty. Five models are individually constructed timeframes illustrate dynamics compared seven evaluation indexes demonstrate effectiveness proposed BN model. It, for first time, investigates changing roles with time. The insights gained from this invaluable, contributing improved prediction strategies acknowledging patterns accidents.

Language: Английский

Citations

45
Risk-informed multi-objective decision-making of emergency schemes optimization DOI
Xuan Liu, Cheng Wang,

Zhiming Yin

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 245, P. 109979 - 109979

Published: Feb. 3, 2024

Language: Английский

Citations

26
Navigating uncertainty: A dynamic Bayesian network-based risk assessment framework for maritime trade routes DOI
Hanwen Fan,

Haiying Jia,

Xuzhuo He

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 250, P. 110311 - 110311

Published: July 1, 2024

Language: Английский

Citations

22
Coupling and causation analysis of risk influencing factors for navigational accidents in ice-covered waters DOI
Shanshan Fu, Mingyan Wu, Yue Zhang

et al.

Ocean Engineering, Journal Year: 2025, Volume and Issue: 320, P. 120280 - 120280

Published: Jan. 8, 2025

Language: Английский

Citations

3
An integrated resilience assessment methodology for emergency response systems based on multi-stage STAMP and dynamic Bayesian networks DOI
Xu An,

Zhiming Yin,

Qi Tong

et al.

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 238, P. 109445 - 109445

Published: June 16, 2023

Language: Английский

Citations

42
A novel methodology to model disruption propagation for resilient maritime transportation systems–a case study of the Arctic maritime transportation system DOI

Yang Liu,

Xiaoxue Ma, Weiliang Qiao

et al.

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 241, P. 109620 - 109620

Published: Sept. 3, 2023

Language: Английский

Citations

28
Reliability-based maintenance optimization of long-distance oil and gas transmission pipeline networks DOI
Bilal Zerouali,

Yacine Sahraoui,

Mourad Nahal

et al.

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 249, P. 110236 - 110236

Published: May 22, 2024

Language: Английский

Citations

14
Quantitive HAZOP and D-S evidence theory-fault tree analysis approach to predict fire and explosion risk in inert gas system on-board tanker ship DOI
Ozcan Durukan, Emre Akyüz, Orhan Destanoğlu

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 308, P. 118274 - 118274

Published: May 27, 2024

Language: Английский

Citations

13