Degradation prediction and explainable analyses of the corroded subsea pipelines based on INSGAII-PGNN and SHAP algorithm DOI
Qian Chen, Huang Wei, Ya Wen

и другие.

Ocean Engineering, Год журнала: 2025, Номер 334, С. 121495 - 121495

Опубликована: Май 26, 2025

Язык: Английский

Modeling the effect of multi-factor coupled emergency response on domino effects in LNG storage tank areas using intuitionistic fuzzy hierarchical analysis and Bayesian network DOI
Jianxing Yu,

Hongyu Ding,

Qingze Zeng

и другие.

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 107095 - 107095

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

1
Study on disaster-causing probability evaluation of gas pipeline in karst area DOI Creative Commons
Qiao-Chu Li, Peng Zhang

PLoS ONE, Год журнала: 2025, Номер 20(2), С. e0316820 - e0316820

Опубликована: Фев. 3, 2025

In this paper, a disaster-causing probability evaluation method of gas pipelines in karst areas based on disaster system theory and vulnerability is proposed. The hazard index pipeline events established from three aspects: the activity disaster-prone environment, risk factors disaster-bearing bodies. Combined with advantages information transmission updating Bayesian network model, gradually calculated multi-level perspective. Based structural reliability theory, function by considering interaction between intensity resistance ability. Meanwhile, design checkpoint finite element simulation are used to calculate probability. Finally, new approach for formed, which comprehensively considers event vulnerability. work presented paper can provide reference safety management accident prevention crossing areas.

Язык: Английский

Процитировано

0
Self-organized criticality study in natural gas pipeline systems: A system & data science approach DOI
Zhaoming Yang, Zhiwei Zhao, Qi Xiang

и другие.

Applied Energy, Год журнала: 2025, Номер 387, С. 125624 - 125624

Опубликована: Март 3, 2025

Язык: Английский

Процитировано

0
A data-driven method for pipeline inhibition efficiency prediction and risk assessment based on MPF-GCA-FPT-FRA approach DOI
Guoxi He,

Pan Jiang,

Kexi Liao

и другие.

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 106980 - 106980

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Probability Analysis of Hazardous Chemicals Storage Tank Leakage Accident Based on Neural Network and Fuzzy Dynamic Fault Tree DOI Creative Commons
Xue Li,

Wei’ao Liu,

Ning Zhou

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(7), С. 3504 - 3504

Опубликована: Март 23, 2025

Aiming at the problems of complex calculation processes, insufficient risk data, and reliance on experts’ subjective judgments that exist in traditional probability analysis methods, this paper proposes a method for hazardous chemical storage tank leakage accidents based neural networks fuzzy dynamic fault trees (Fuzzy DFT). This combines set theory (FST) Bootstrap technology to accurately quantify failure probabilities basic events (BEs) reduce dependence judgments. Furthermore, an artificial network (ANN) model failures is constructed. can calculate by taking into account dependency relationships among events. Finally, long short-term memory (LSTM) utilized analyze evolution trend over time. In paper, applied case “11.28” Shenghua vinyl chloride accident. The results show are highly consistent with actual situation accident, indicating it scientific effective analyzing accidents.

Язык: Английский

Процитировано

0
Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network DOI Creative Commons
Chao Liu,

Chuankun Zhou,

Hongyan Wang

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 4, 2025

Subsea pipeline system faces significant challenges in practical engineering applications, including complexity, environmental variability, and limited historical data. These factors complicate the accurate estimation of component failure rates, leading to fault polymorphism inherent uncertainty. To address these challenges, this study proposes a reliability analysis method based on Fuzzy Polymorphic Bayesian Network (FPBN). The approach utilizes multi-state tree construct polymorphic (BN), integrating traditional BN techniques with consideration multiple states fuzzy rates. This extension allows network handle uncertainties such as imprecise data unclear logical relationships. is applied subsea risk by developing model. Through quantitative analysis, probability calculated. Reverse diagnosis then conducted determine posterior probabilities root nodes identify vulnerabilities. results demonstrate that FPBN effectively addresses ambiguity uncertainty providing robust framework applications.

Язык: Английский

Процитировано

0
Mixing mechanisms of hydrogen-blended natural gas in subsea pipelines: Effects of injection angles DOI
Fenghui Han,

X. C. Mu,

Yintao Wei

и другие.

Ocean Engineering, Год журнала: 2025, Номер 330, С. 121245 - 121245

Опубликована: Апрель 18, 2025

Язык: Английский

Процитировано

0
Simulation Analysis on the Influence Factors of Erosion Damage of Typical Elbows in Gathering and Transportation Pipelines DOI
Qiang Zeng,

Wenhao Que,

Jinjin Wang

и другие.

Journal of Pipeline Systems Engineering and Practice, Год журнала: 2025, Номер 16(3)

Опубликована: Май 5, 2025

Язык: Английский

Процитировано

0
Degradation prediction and explainable analyses of the corroded subsea pipelines based on INSGAII-PGNN and SHAP algorithm DOI
Qian Chen, Huang Wei, Ya Wen

и другие.

Ocean Engineering, Год журнала: 2025, Номер 334, С. 121495 - 121495

Опубликована: Май 26, 2025

Язык: Английский

Процитировано

0