Reliability Engineering & System Safety最新文献

{"title":"Improving reliability of safety countermeasure evaluation at highway-rail grade crossings through aleatoric uncertainty modeling with machine learning techniques","authors":"Mohammadali Zayandehroodi ,&nbsp;Barat Mojaradi ,&nbsp;Morteza Bagheri","doi":"10.1016/j.ress.2025.111082","DOIUrl":"10.1016/j.ress.2025.111082","url":null,"abstract":"<div><div>Traditional Collision Modification Factor (CMF) calculation methods rely on simplistic statistical models that often fail to account for the complex, non-linear relationships influencing collision rates, leading to uncertain estimates. To address this gap, this study aims to improve the reliability of CMF estimation for safety countermeasures by introducing a novel hybrid model that combines Negative Binomial (NB) regression with a Long Short-Term Memory (LSTM) neural network to estimate aleatoric uncertainty. In other words, the proposed method integrates statistical modelling with machine learning techniques within the Empirical Bayes (EB) framework to compute uncertainty for enhancing CMF accuracy and stability. By increasing the reliability of collision frequency predictions and calculating more precise CMFs, the proposed method enables the selection of appropriate countermeasures, ultimately reducing fatalities and costs. The model is trained using data from Highway-Rail Grade Crossings (HRGC) inventory and collision records from the Federal Railroad Administration (FRA) for 2016–2022. The NB regression model provides a statistical foundation for collision prediction, while the LSTM component models uncertainties, significantly improve CMF calculation. Compared to the traditional NB model, the hybrid NB-LSTM approach reduces root mean squared error (RMSE) by 62.5 % and mean absolute error (MAE) by 61 % in predicting collision frequencies, leading to more reliable CMFs. The model identifies that gates reduce collisions by 61 % in high-traffic HRGCs, bells decrease collisions by 67 % in high-speed areas, and flashing lights achieve a 72 % reduction in low-traffic, high-speed crossings. Additionally, the proposed method achieves lower standard errors (S.E.) across all countermeasures.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111082"},"PeriodicalIF":9.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747722","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}

{"title":"A methodology of natural gas pipeline network system supply resilience optimization: Based on demand-side and data science-driven approach","authors":"Zhiwei Zhao ,&nbsp;Zhaoming Yang ,&nbsp;Huai Su ,&nbsp;Michael H. Faber ,&nbsp;Jinjun Zhang","doi":"10.1016/j.ress.2025.111071","DOIUrl":"10.1016/j.ress.2025.111071","url":null,"abstract":"<div><div>This paper proposes a method for optimizing the supply resilience of natural gas pipeline networks, driven by demand-side dynamics and data science. The method is divided into two main components: user demand characteristic modeling and system supply resilience optimization modeling. In the user demand characteristic modeling phase, preprocessed user demand data is used, combining the Tabular Variational Autoencoder (TVAE) with probability density distribution curve fitting to provide an in-depth characterization of user demand patterns. For the system supply resilience optimization modeling, constraints are established based on the functional characteristics of the system's components, and specific objective functions are designed for different operational scenarios. Additionally, the Latin Hypercube Sampling (LHS) method is employed to capture fluctuations in user demand. Finally, this paper introduces a set of evaluation indicators for gas supply resilience and validates the proposed methodology through five scenario-based case studies. The results confirm the effectiveness and feasibility of this approach in improving the resilience of natural gas pipeline systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111071"},"PeriodicalIF":9.4,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747723","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}

{"title":"Domain generalization network based on inter-domain multivariate linearization for intelligent fault diagnosis","authors":"Wei Guan ,&nbsp;Shuai Wang ,&nbsp;Zeren Chen ,&nbsp;Guoqiang Wang ,&nbsp;Zhengbin Liu ,&nbsp;Da Cui ,&nbsp;Yiwei Mao","doi":"10.1016/j.ress.2025.111055","DOIUrl":"10.1016/j.ress.2025.111055","url":null,"abstract":"<div><div>Intelligent fault diagnosis technology determines the safety and reliability of equipment operation, and domain-based adaptive fault diagnosis models have been explored for solving the problem of data distribution discrepancies caused by different operating conditions. However, the requirement of obtaining the unlabeled target domain data in advance limits its application in real-world equipment operating scenarios. To address this problem, this paper proposes an inter-domain multivariate linearization (IML)-guided domain generalization network (IMLNet) for intelligent fault diagnosis. A domain multivariate fusion generation module is designed to construct new domains by linearizing between different domains using inter-domain multivariate linearization, which helps the network to extract domain invariant features in depth. Meanwhile, by fusing the multi-attention mechanism and feature pyramid network on the basis of residual network, it promotes the network to capture multi-scale information and provide richer semantic information. The effectiveness of the method is verified through two different fault diagnosis cases.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111055"},"PeriodicalIF":9.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739303","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}

{"title":"Fault semantic knowledge transfer learning: Cross-domain compound fault diagnosis method under limited single fault samples","authors":"Huaitao Xia ,&nbsp;Tao Meng ,&nbsp;Zonglin Zuo ,&nbsp;Wenjie Ma","doi":"10.1016/j.ress.2025.111050","DOIUrl":"10.1016/j.ress.2025.111050","url":null,"abstract":"<div><div>The coupling of faults leads to an exponential growth of compound fault types, making it impractical to collect complete labeled compound fault data in real-world scenarios. While cross-domain compound fault diagnosis (the target-domain does not have labeled compound fault data) is crucial for system reliability, existing methods often rely on abundant single-fault samples and rarely validate the reliability when single-fault data is limited. To overcome this limitation, we propose a novel fault semantic knowledge transfer learning framework. Specifically, FSKTL incorporates inter-class semantic distance loss in the source-domain, enabling fault classification through low-dimensional fault semantics and identifying the optimal fault semantic correlation function. Subsequently, FSKTL introduces inter-domain semantic alignment loss in the target-domain. This approach not only preserves the semantic space optimized by the source-domain for fault classification, but also achieves domain adaptation, enhancing the cross-domain generalization of the optimal fault semantic correlation function. Finally, extensive experiments are conducted on two publicly available datasets to validate the effectiveness of the proposed method. The results demonstrate that compared to other methods, this approach achieves the highest accuracy in cross-domain compound and single fault diagnosis.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111050"},"PeriodicalIF":9.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747434","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}

{"title":"Applying incremental learning in binary-addition-tree algorithm in reliability analysis of dynamic binary-state networks","authors":"Zhifeng Hao ,&nbsp;Wei-Chang Yeh","doi":"10.1016/j.ress.2025.111072","DOIUrl":"10.1016/j.ress.2025.111072","url":null,"abstract":"<div><div>This paper presents a novel approach to enhance the Binary-Addition-Tree algorithm (BAT) by integrating incremental learning techniques. BAT, known for its simplicity in development, implementation, and application, is a powerful implicit enumeration method for solving network reliability and optimization problems. However, it traditionally struggles with dynamic and large-scale networks due to its static nature. By introducing incremental learning, we enable the BAT to adapt and improve its performance iteratively as it encounters new data or network changes. This integration allows for more efficient computation, reduces redundancy without searching for minimal paths and cuts, and improves overall performance in dynamic environments. Experimental results demonstrate the effectiveness of the proposed method, showing significant improvements in both computational efficiency and solution quality compared to the traditional BAT and indirect algorithms, such as MP (minimal path) -based algorithms and MC (minimal cut) -based algorithms.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111072"},"PeriodicalIF":9.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747721","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}

{"title":"Two-stage stochastic optimization of passenger evacuation routes in metro stations considering stampede incidents","authors":"Yi Yang,&nbsp;Dong-Fan Xie,&nbsp;Xiao-Mei Zhao,&nbsp;Bin Jia","doi":"10.1016/j.ress.2025.111047","DOIUrl":"10.1016/j.ress.2025.111047","url":null,"abstract":"<div><div>Stampede incidents frequently occur in densely populated metro stations during emergencies, and if not promptly addressed, they can cause more severe cascading effects, resulting in passenger injuries and even deaths. To address this issue, this study proposes a two-stage stochastic optimization model that incorporates the occurrence of unpredictable stampedes to effectively plan individualized evacuation routes for passengers. The model aims to minimize evacuation time by optimizing both the initial evacuation routes of passengers and the subsequent routes after stampede incidents, thereby mitigating passenger congestion in bottleneck areas and providing passengers with alternative destinations. By introducing auxiliary variables, the model is reformulated to reduce the constraints. The model is tested under various stampede scenarios. The results indicate that the proposed optimization strategy can significantly reduce evacuation time, as well as the density in bottleneck area of the metro station, regardless of the severity of stampede incidents. Via comprehensive sensitivity analysis, the critical factors having a significant impact on the evacuation process have been identified. This finding is expected to provide valuable insights for regulatory agencies in the effective implementation of evacuation strategies.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111047"},"PeriodicalIF":9.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747433","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}

{"title":"Stochastic programming on joint optimization of redundancy design and condition-based maintenance for continuously degrading systems subject to uncertain usage stresses","authors":"Xiaoyan Zhu ,&nbsp;Yaqian Hao ,&nbsp;Suk Joo Bae","doi":"10.1016/j.ress.2025.111023","DOIUrl":"10.1016/j.ress.2025.111023","url":null,"abstract":"<div><div>This study investigates the joint optimization of system redundancy design and maintenance policies under uncertain usage stresses, using various stochastic programming models and stochastic-degradation-based reliability models. It is the first to address condition-based maintenance (CBM) policies, which outperform traditional age-based maintenance by reducing over- and tardy maintenance. Three two-stage stochastic programming models are developed. The first is a risk-neutral model aiming to minimize the expected system life-cycle cost across various usage stresses. The second is a risk-averse model using conditional value-at-risk to find solutions that perform well under the worst stresses. The third model also employs a risk-averse approach, using the upper partial mean to seek robust solutions for adverse stresses. The first-stage decision variables are subsystem redundancy levels, influencing CBM policies in the second stage. These CBM decisions depend on subsystem degradation levels and usage stresses. The long-run maintenance and failure cost rate is modeled as a recourse function, affecting redundancy allocation decisions. A numerical study demonstrates that the risk-averse strategies effectively mitigate the cost of worst scenarios without significantly increasing expected system life-cycle cost over all the scenarios. The redundancy level is high under a high risk aversion and can remain stable in a certain range of risk aversion. When the risk aversion is minor and the primary goal is the lowest expected lifetime-cycle cost, the redundancy design from risk-neutral model is preferred. The two risk-averse models would not generate the same redundancy design, no matter how to adjust the risk-averse parameters in the two models. Thus, the two risk-averse methods cannot be used exchangeable. The model using conditional value-at-risk is suitable for the cases where severe usage stresses could happen and the bad consequence cannot be tolerated. The model with upper partial mean is good for stabilizing the performances under all the adverse scenarios.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111023"},"PeriodicalIF":9.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734650","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}

{"title":"Multi-objective disintegration of multilayer networks","authors":"Mingze Qi ,&nbsp;Peng Chen ,&nbsp;Yuan Liang ,&nbsp;Xiaohan Li ,&nbsp;Hongzhong Deng ,&nbsp;Xiaojun Duan","doi":"10.1016/j.ress.2025.111042","DOIUrl":"10.1016/j.ress.2025.111042","url":null,"abstract":"<div><div>The multiple relationships between nodes in complex systems or the dependencies between multiple subsystems can be effectively represented by multilayer networks. The network disintegration problem seeks to identify a set of nodes whose removal can minimize network performance. Existing research on the disintegration of multilayer networks often focuses on overall network connectivity. This study examines the multi-objective disintegration problem of multilayer networks to find groups of nodes that maximize damage to different layers. The multi-objective optimization model is established, and the nondominated sorting genetic algorithm is improved to solve it. The search efficiency for approximating the Pareto front is enhanced by innovating initial population generation and crossover operation coding methods. Additionally, we employ the technique for order preference by similarity to ideal solution to assess the effectiveness of various multi-objective disintegration strategies. Experiments in the model and real multilayer networks show that the relative optimal strategy in the Pareto solution set can effectively balance the disintegration effect of different layers. This research offers valuable insight into safeguarding infrastructure systems and controlling disease transmission.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111042"},"PeriodicalIF":9.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A prior knowledge-guided predictive framework for LCF life and its implementation in shaft-like components under multiaxial loading","authors":"Butong Li,&nbsp;Junjie Zhu,&nbsp;Xufeng Zhao","doi":"10.1016/j.ress.2025.111044","DOIUrl":"10.1016/j.ress.2025.111044","url":null,"abstract":"<div><div>Predicting low-cycle fatigue (LCF) life under complex loading conditions has long been a challenge. Reliable fatigue life prediction is crucial for the fatigue reliability assessment of industrial components. This paper proposes a prior knowledge-guided framework for predicting LCF life under multiaxial loading conditions. The framework integrates physical knowledge and partial known relationships. Inspired by concepts from reliability-based design optimization (RBDO), the framework is capable of predicting deterministic and probabilistic LCF life with greater efficiency and accuracy. Building on this, we discuss the LCF life degradation of components under survival rates by introducing the multiaxial fatigue parameter. The parameter can effectively describe the trends of LCF life under elliptical multiaxial loading paths. Furthermore, the hazard rate and fatigue reliability of structural components is investigated. The research presented in this paper can offer valuable guidance for applications in practical industrial contexts.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111044"},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724797","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}

{"title":"Preventive replacement policies of parallel/series systems with dependent components under deviation costs","authors":"Jiale Niu ,&nbsp;Rongfang Yan ,&nbsp;Jiandong Zhang","doi":"10.1016/j.ress.2025.111033","DOIUrl":"10.1016/j.ress.2025.111033","url":null,"abstract":"<div><div>In traditional reliability analysis, an important assumption is that the failure components are independent from one another. However, this assumption is often challenged in reliability engineering as practical failure process is always dependent on one another component. This manuscript bases on the method of copula to characterize the dependence of the components lifetime, and studies the preventive replacement policies of series/parallel systems with dependent heterogeneous components under deviation costs. Firstly, we provide the optimal replacement time of the series and parallel systems from dependent components in the age replacement policies under the deviation cost. Secondly, we give the optimal number of periods for series/parallel systems with dependent components to minimize the expected cost rate under deviation costs. The effects of dependency, deviation costs, and the number of components in the system on the maintenance policies are analyzed. The numerical examples are then implemented to develop the optimal preventive replacement policies that minimize the expected cost rate. A case study of the cables in high-voltage transmission networks system from dependent components is conducted to present the optimal replacement time and number of periods.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"260 ","pages":"Article 111033"},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714826","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}