Reliability Engineering & System Safety最新文献_第2页

Topological analysis of risks in hazardous materials transportation systems using fitness landscape theory and association rules mining 基于适应度景观理论和关联规则挖掘的危险品运输系统风险拓扑分析

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-25 DOI: 10.1016/j.ress.2025.111396

Jian Guo , Kaijiang Ma , Haoxuan Ren

{"title":"Topological analysis of risks in hazardous materials transportation systems using fitness landscape theory and association rules mining","authors":"Jian Guo , Kaijiang Ma , Haoxuan Ren","doi":"10.1016/j.ress.2025.111396","DOIUrl":"10.1016/j.ress.2025.111396","url":null,"abstract":"<div><div>Determining the failure modes of hazardous materials transportation systems, considering the coupled effects of risk factors, is crucial for ensuring transportation safety. This study proposes a coupled topological analysis method for hazardous materials road transport risks, based on association rule mining and fitness landscape theory. This method can reflect the correlations and evolutionary patterns of risk factors, thereby providing a basis for formulating risk mitigation strategies. Firstly, text mining techniques are employed to identify critical risk factors and gather a structured dataset comprising 165 entries. Secondly, association rule algorithms are used to uncover potential relationships among sub-factors, employing the Apriori algorithm with set thresholds to extract strong association rules, which are then mapped into a landscape model depicting the coupled evolution of system risk factors. Finally, by employing a defined fitness function, typical system failure paths are further analyzed topologically. The results indicate that directly mining failure paths from sub-risk factors can elucidate more detailed system failure mechanisms. Coupled failure modes involving human and environmental factors warrant particular attention. Vehicle factors often lead to accidents without further evolution, necessitating the establishment of corresponding inspection mechanisms.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111396"},"PeriodicalIF":9.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144510985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced statistical analysis and system reliability assessment of API 5L steel pipelines subjected to corrosion attack API 5L钢管道受腐蚀的先进统计分析和系统可靠性评估

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-24 DOI: 10.1016/j.ress.2025.111387

Djamel Zelmati , Omar Bouledroua , Oualid Ghelloudj , Riad Harouz

{"title":"Advanced statistical analysis and system reliability assessment of API 5L steel pipelines subjected to corrosion attack","authors":"Djamel Zelmati , Omar Bouledroua , Oualid Ghelloudj , Riad Harouz","doi":"10.1016/j.ress.2025.111387","DOIUrl":"10.1016/j.ress.2025.111387","url":null,"abstract":"<div><div>It is crucial to note that developing a maintenance and repair strategy by statistically consolidating the corrosion features across the pipeline length ultimately yields a single probability of failure for the entire line, potentially obscuring the distinct statistical behavior of individual pipe segments. Since the corrosion profiles in different segments of the pipeline are statistically correlated, failure in one section can affect neighboring sections, which defines the overall system reliability. In this study, the remaining strength of a corroded pipeline was estimated using the Failure Assessment Diagram (FAD). A comprehensive statistical analysis identified the typical probability density functions of all random variables in the failure scenario, as well as their standard deviations and typical correlation coefficients. A Monte Carlo simulation (MCS) was integrated with the SINTAP procedure to construct a probabilistic FAD. Sensitivity analysis revealed the relative influence of each variable on the pipeline’s remaining strength, emphasizing a strong interaction between defect depth and wall thickness. Additionally, the combined effect of the operating pressure and the coefficient of variation of the corrosion defect depth was evaluated to understand their influence on the probability of failure. Furthermore, system reliability assessment allows for more precise risk management, avoiding overly conservative or optimistic estimates that might arise from treating the entire pipeline as a single unit. Besides, the developed procedure for global system reliability can be used to devise optimal and more accurate inspection and maintenance schedules.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111387"},"PeriodicalIF":9.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reliability assessment methods considering failure correlation and importance analysis for multiple progressive damage 考虑失效相关性和重要性分析的多重渐进损伤可靠性评估方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-24 DOI: 10.1016/j.ress.2025.111389

Zhixuan Gao , Deyin Jiang , Xinchen Zhuang , Weimin Cui , Tianxiang Yu

{"title":"Reliability assessment methods considering failure correlation and importance analysis for multiple progressive damage","authors":"Zhixuan Gao , Deyin Jiang , Xinchen Zhuang , Weimin Cui , Tianxiang Yu","doi":"10.1016/j.ress.2025.111389","DOIUrl":"10.1016/j.ress.2025.111389","url":null,"abstract":"<div><div>Aircraft complex mechanisms are susceptible to multiple progressive damage in operation, where a particular form of damage can have an effect on the strength of another through the mechanism transmission. The results of reliability analysis that ignores the correlation between them will deviate from the actual situation. To address the above problems, based on the characteristics of multiple progressive damage, two correlation models of multiple progressive damage are established, and a reliability assessment method considering the correlation of multiple progressive damage is proposed. Based on the vine copula theory, the correlation model of multiple progressive damage systems at different times was established, and the reliability of the system was calculated based on Monte Carlo method. Based on the importance theory, the importance analysis method is further proposed for multiple progressive damage. The results of the engineering case study show that ignoring the correlation between multiple progressive damage can lead to an inaccurate system reliability assessment, the maximum relative error to the reliability results for the independent case is 25 %. And the types of damage that need to be focused on maintenance are obtained by importance analysis, and the method provides a reference for the reliability assessment of complex mechanisms in aerospace.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111389"},"PeriodicalIF":9.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144510986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prioritized fault detection and diagnosis in chemical industry using production loss-guided cost matrix with self-attention mechanism 基于自关注机制的生产损失导向成本矩阵的化工故障优先检测与诊断

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-24 DOI: 10.1016/j.ress.2025.111391

Santi Bardeeniz , Chanin Panjapornpon , Tawesin Jitchaiyapoom , David Shan-Hill Wong , Yuan Yao

{"title":"Prioritized fault detection and diagnosis in chemical industry using production loss-guided cost matrix with self-attention mechanism","authors":"Santi Bardeeniz , Chanin Panjapornpon , Tawesin Jitchaiyapoom , David Shan-Hill Wong , Yuan Yao","doi":"10.1016/j.ress.2025.111391","DOIUrl":"10.1016/j.ress.2025.111391","url":null,"abstract":"<div><div>Product loss is an ongoing critical challenge in industrial processes, particularly in chemical systems where undetected faults can have major economic consequences. Traditional fault detection models, designed primarily for mechanical systems, often prioritize accuracy and system performance but fail to account for the economic impact of faults in chemical systems. To address this gap, this study proposed a production loss-guided cost matrix self-attention, long short-term memory (PLSA-LSTM) model, which integrates a production loss-guided cost matrix to align fault classification with operational priorities. The cost matrix assigns higher penalties to faults with major production losses, guiding the model to focus on economically critical faults. The self-attention mechanism emphasizes critical input features and Bayesian optimization fine-tunes hyperparameters to balance accuracy and production loss minimization. The PLSA-LSTM model was applied to a glycerin purification process and achieved a fault detection accuracy of 95.31% while reducing production loss by 99.07% per fault occurrence, notably outperforming traditional methods. Compared to the traditional self-attention model, the PLSA-LSTM model reduced unprevented production loss from 94.97 kg/h to 0.87 kg/h while maintaining competitive classification performance. The results demonstrated the ability of the model to handle complex fault scenarios, prioritize faults with high economic impact, and minimize production losses, making it highly applicable to fault-prone industrial environments.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111391"},"PeriodicalIF":9.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-constant imperfect maintenance effects in Inverse Gaussian degradation models for multiple repairable systems 多可修系统反高斯退化模型中的非常不完全维护效应

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-24 DOI: 10.1016/j.ress.2025.111349

Adriane Caroline Teixeira Portela , Lia Hanna Martins Morita , Vera Tomazella , Maria Luíza Toledo , Paulo Henrique Ferreira , Francisco Louzada

{"title":"Non-constant imperfect maintenance effects in Inverse Gaussian degradation models for multiple repairable systems","authors":"Adriane Caroline Teixeira Portela , Lia Hanna Martins Morita , Vera Tomazella , Maria Luíza Toledo , Paulo Henrique Ferreira , Francisco Louzada","doi":"10.1016/j.ress.2025.111349","DOIUrl":"10.1016/j.ress.2025.111349","url":null,"abstract":"<div><div>This paper proposes a degradation model tailored for multiple repairable systems subject to imperfect maintenance actions, incorporating three key assumptions: (i) the underlying degradation process follows an Inverse Gaussian distribution; (ii) the non-constant effects of imperfect maintenance are modeled using the Arithmetic Reduction of Degradation with memory one <span><math><mrow><mo>(</mo><msub><mrow><mtext>ARD</mtext></mrow><mrow><mn>1</mn></mrow></msub><mo>)</mo></mrow></math></span> framework; and (iii) systems undergo regular inspections, with degradation levels measured immediately before, after, and between inspections. This approach provides a flexible representation of degradation dynamics while accounting for the imperfect nature of maintenance interventions and their evolving impact over time. To evaluate the proposed model, we conduct a simulation study to assess the asymptotic properties of the parameter estimators obtained via the maximum likelihood method. The study demonstrates the robustness and reliability of the estimation process, highlighting the model’s ability to capture the degradation behavior accurately. Additionally, a practical application is presented using real-world data from LASER device degradation under various maintenance scenarios. The ability to account for the effects of imperfect maintenance is especially important as, in practice, repairs rarely return systems to a like-new condition, nor do they leave them as degraded as they were before. The proposed framework contributes to the advancement of degradation modeling, offering a robust tool for reliability engineers and practitioners dealing with repairable systems and imperfect maintenance conditions.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111349"},"PeriodicalIF":9.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Critical node identification of dynamic-load wireless sensor networks for cascading failure protection 基于级联故障保护的动态负载无线传感器网络关键节点识别

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-23 DOI: 10.1016/j.ress.2025.111351

Yifan Yuan , Xiaohong Shen , Lin Sun , Yongsheng Yan , Haiyan Wang

{"title":"Critical node identification of dynamic-load wireless sensor networks for cascading failure protection","authors":"Yifan Yuan , Xiaohong Shen , Lin Sun , Yongsheng Yan , Haiyan Wang","doi":"10.1016/j.ress.2025.111351","DOIUrl":"10.1016/j.ress.2025.111351","url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs), as complex and dynamic systems, are highly susceptible to cascading failures. To enhance network resilience, this study addresses the identification of critical nodes that drive failure propagation. Unlike prior studies that often ignore the impact of varying network load, we highlight that node importance can change significantly under dynamic load conditions. To tackle this, we introduce a method for identifying critical nodes in dynamic-load WSNs. We first construct a cascading failure model that links network load with link capacity, analyzing how fluctuations in load affect failure propagation. Building on this model, we propose an EW-TOPSIS-based node evaluation method grounded in node deletion, where the influence of each node under different load conditions is considered as distinct evaluation criteria. To verify the proposed method, we conduct simulations of low-rate underwater WSNs in ns-3 under dynamic load conditions. Results show that, as an attack node selection strategy, our method achieves up to 30% and 25% greater degradation in failure severity and PDR, respectively, across varying network topology, densities and traffic conditions, compared to five baseline techniques. This work provides insights for designing effective mitigation strategies against cascading failures in resource-constrained networks.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111351"},"PeriodicalIF":9.4,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving power distribution system reliability via optimized Microgrid integration and storage management 通过优化微网集成和存储管理，提高配电系统可靠性

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-22 DOI: 10.1016/j.ress.2025.111386

Amer Aščerić , Marko Čepin

{"title":"Improving power distribution system reliability via optimized Microgrid integration and storage management","authors":"Amer Aščerić , Marko Čepin","doi":"10.1016/j.ress.2025.111386","DOIUrl":"10.1016/j.ress.2025.111386","url":null,"abstract":"<div><div>Modern power distribution systems are increasingly incorporating volatile renewable energy sources and distribution system operators need to develop suitable measures to ensure power system reliability and stability under all circumstances. The objective of the work is to develop an optimization methodology to improve the efficiency and reliability of power distribution systems by integrating microgrids and auxiliary services. The approach utilizes a genetic algorithm to optimize energy exchanges between microgrids and the grid, aiming to reduce congestion, alleviate line overloads, minimize penalty costs for the distribution system operator, and enhance the integration of renewable energy sources. The results show how optimized energy exchange and the strategic use of auxiliary services can improve grid stability and reliability while creating economic benefits for both the distribution system operator and the microgrid owners. Specifically, the optimized system reduced the number of time steps during which one or more lines were overloaded from 10,172 to 2793, improving the reliability coefficient from 0.05788 to 0.08215. Penalties incurred by DSO due to network congestion were reduced by over 75 %, resulting in substantial financial savings. Furthermore, the results highlight the broader potential of such methods to support the transition to more resilient, efficient, and cooperative power distribution systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111386"},"PeriodicalIF":9.4,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep reinforcement learning for joint optimization of maintenance and spare parts ordering considering spare parts supply uncertainty

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-22 DOI: 10.1016/j.ress.2025.111385

Yunxin Zhu , Meimei Zheng , Zhiyun Su , Tangbin Xia , Jie Lin , Ershun Pan

{"title":"Deep reinforcement learning for joint optimization of maintenance and spare parts ordering considering spare parts supply uncertainty","authors":"Yunxin Zhu , Meimei Zheng , Zhiyun Su , Tangbin Xia , Jie Lin , Ershun Pan","doi":"10.1016/j.ress.2025.111385","DOIUrl":"10.1016/j.ress.2025.111385","url":null,"abstract":"<div><div>Efficient maintenance and spare parts ordering strategies can reduce costs for manufacturing companies. In recent years, important components may suffer supply risks due to geopolitical conflicts, trade conflicts, and limitations of key resources. This paper investigates the joint optimization of condition-based maintenance and dual sourcing of spare parts from reliable and unreliable suppliers. We formulate this joint decision problem with a Markov decision process and design a value iteration algorithm to obtain exact solutions for the optimal maintenance and ordering policy. However, the value iteration algorithm is not suitable for solving large-scale problems due to its long running time. Thus, we develop a deep Q-network (DQN) algorithm based on deep reinforcement learning to improve computation efficiency. Numerical experiments are conducted to validate the effectiveness of the DQN algorithm. The results show that the DQN algorithm can reduce the running time by 92.58 % for systems with more than 4 components and more than 5 states within a 4.82 % cost gap compared to the value iteration algorithm. Compared to the separate heuristic policy, the DQN algorithm can averagely reduce the cost by 11.27 %.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111385"},"PeriodicalIF":9.4,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incorporation of knowledge and data-driven models applied in shield tunneling: A review 知识与数据驱动模型在盾构掘进中的应用综述

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-21 DOI: 10.1016/j.ress.2025.111379

Zhechen Zhang , Hanbin Luo , Jiajing Liu

{"title":"Incorporation of knowledge and data-driven models applied in shield tunneling: A review","authors":"Zhechen Zhang , Hanbin Luo , Jiajing Liu","doi":"10.1016/j.ress.2025.111379","DOIUrl":"10.1016/j.ress.2025.111379","url":null,"abstract":"<div><div>Data-driven models have undergone extensive exploration in addressing shield tunneling challenges, propelled by advancements in sensing technology and machine learning (ML) techniques. However, relying solely on data-driven approaches for shield tunneling control presents issues of physical inconsistency, poor interpretability, and a reliance on high-quality and sufficient data. This review meticulously examines the optimization of ML models through the integration of knowledge, tailored to the shield tunneling domain. First, the types of knowledge involved, encompassing world knowledge, scientific knowledge, and empirical laws, are defined and elucidated. Second, existing practices aimed at tackling main issues within this domain, including environmental impacts, geological conditions, and shield operation performance, are elaborated. Subsequently, the fusion strategies based on the ML pipeline are exploited. Building upon this, the challenges and future directions of this innovative model, including knowledge compilation and utilization, model development and evaluation, and practical application in shield construction are discussed. This review deepens the understanding of data and knowledge fusion methods, providing new insights into the development of this approach for aiding in shield tunnel projects.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111379"},"PeriodicalIF":9.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new method of interval Bayesian penalized network for gravelly soil seismic liquefaction prediction considering parameter confidence and model flaws uncertainties 考虑参数置信度和模型缺陷不确定性的区间贝叶斯惩罚网络砂质土地震液化预测新方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-06-21 DOI: 10.1016/j.ress.2025.111383

Jing Wang , Jilei Hu

{"title":"A new method of interval Bayesian penalized network for gravelly soil seismic liquefaction prediction considering parameter confidence and model flaws uncertainties","authors":"Jing Wang , Jilei Hu","doi":"10.1016/j.ress.2025.111383","DOIUrl":"10.1016/j.ress.2025.111383","url":null,"abstract":"<div><div>Seismic liquefaction prediction of gravelly soils is a complex systematic problem involving multiple uncertainties. Existing studies ignore the parameter confidence uncertainty introduced during the simplification of liquefaction field test data and the model flaws in the model uncertainty. This study proposes a new Interval Bayesian Penalty Network (IBPN) method. The IBPN characterizes, employing interval probabilities, the parameter uncertainty introduced by using the mean value to represent the whole critical liquefiable soil layer when the data are simplified, and subsequently dynamically optimize false negative and false positive errors in liquefaction predictions by introducing a risk-sensitive penalty function. By comparing with five existing methods, including those that consider the uncertainties, the results show that the IBPN method significantly outperforms the other algorithms in terms of prediction accuracy after simultaneously resolving the uncertainties caused by data simplification and prediction errors. The discussion revealed that considering parameter uncertainty is more important than consideration of model flaws for improving prediction accuracy. In addition, the validation of new historical seismic liquefaction data demonstrates the effectiveness and generalization ability of the IBPN method. This work not only provides a more accurate tool for gravelly soil liquefaction risk assessment but also suggests new research ideas for dealing with complex uncertain systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111383"},"PeriodicalIF":9.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0