Reliability Engineering & System Safety最新文献

{"title":"Resource allocation approaches for improving safety and operations at level crossings: State of the art, existing challenges, and future research needs","authors":"Payam Afkhami ,&nbsp;Razieh Khayamim ,&nbsp;Bokang Li ,&nbsp;Marta Borowska-Stefańska ,&nbsp;Szymon Wiśniewski ,&nbsp;Amir M. Fathollahi-Fard ,&nbsp;Yui-yip Lau ,&nbsp;Maxim A. Dulebenets","doi":"10.1016/j.ress.2025.110839","DOIUrl":"10.1016/j.ress.2025.110839","url":null,"abstract":"<div><div>Level crossings (LCs) present substantial safety challenges due to their unique role as intersections where road and rail traffic meet at the same elevation. This study provides a comprehensive review and analysis of resource allocation studies aimed at enhancing safety and operational efficiency at LC locations. The collected studies are categorized into three main groups, including resource allocation for countermeasure implementation, resource allocation for crossing closures, and resource allocation for constructing grade separations. Each group of studies is systematically reviewed focusing on the evaluated fields, countermeasure considerations, sustainability considerations, sustainability dimensions, methodologies used, and case studies. By synthesizing the current literature, this study highlights the strengths and weaknesses of various strategies, emphasizing the need for a holistic framework that integrates safety, economic, and environmental sustainability dimensions. The key contributions include a detailed evaluation of mathematical optimization models for selecting LCs for resource allocation, consideration of important practical factors associated with resource allocation decisions, safety enhancement costs, collision risk levels, and community engagement. The findings suggest that safety performance, design, and upgrades are the most common fields evaluated by the existing studies. A substantial number of studies on LC closures and grade separations also capture traffic delays in decision making. Moreover, essential future research directions for countermeasure implementation, crossing closures, and grade separations are presented as well. This study can serve as a valuable point of reference for researchers and practitioners in the field of LC safety and operational enhancement by consolidating diverse findings and methodologies from the existing research.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110839"},"PeriodicalIF":9.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143219611","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 hybrid physics informed predictive scheme for predicting low-cycle fatigue life and reliability of aerospace materials under multiaxial loading conditions","authors":"Butong Li,&nbsp;Junjie Zhu,&nbsp;Xufeng Zhao","doi":"10.1016/j.ress.2025.110838","DOIUrl":"10.1016/j.ress.2025.110838","url":null,"abstract":"<div><div>Engineering components such as engine blades, turbofans, external parts, etc., are often subjected to complex loads in the serving environment. Fatigue failure of components under multiaxial loading will occur, causing a severe influence on operational safety. Centered on low-cycle fatigue under multiaxial loading conditions, we have developed a novel fatigue life prediction framework, which utilizes the physics-guided machine learning approach as a surrogate model for fatigue life prediction. We conducted preliminary experiments to obtain the material's mechanical properties and established reliable finite element analysis (FEA) models based on these properties. Subsequently, we generated high-confidence datasets using the FEA models. By leveraging the strengths of both deep learning methods and LightGBM, we proposed a fusion surrogate model called DL-LGBM-DRS. The DL-LGBM-DRS can efficiently and accurately predict low-cycle fatigue life under various multiaxial loading conditions. Lastly, we defined a new fatigue life degradation relationship, KBM-N, using Brown-Miller parameters and fitted probabilistic fatigue life degradation curves based on the KBM-N relations.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110838"},"PeriodicalIF":9.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143219618","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":"Safety risk assessment for connected and automated vehicles: Integrating FTA and CM-improved AHP","authors":"Xiangyu Zheng ,&nbsp;Qi Liu ,&nbsp;Yufeng Li ,&nbsp;Bo Wang ,&nbsp;Wutao Qin","doi":"10.1016/j.ress.2025.110822","DOIUrl":"10.1016/j.ress.2025.110822","url":null,"abstract":"<div><div>To reduce safety accidents from functional failures in connected and automated vehicles (CAVs), risk assessment and prevention are essential. However, traditional hazard analysis and risk assessment (HARA) methods suffer from limitations: insufficient quantitative assessment and inadequate consideration of ambiguity and uncertainty. To this end, we propose a quantitative risk assessment method for CAVs based on fault tree analysis (FTA) and cloud model (CM)-improved analytic hierarchy process (AHP). First, we use the golden section method and CM to refine the automotive safety integrity level (ASIL), representing ambiguity in level boundaries. Next, we incorporate potential functional failure paths and construct basic events for the FTA based on the failure modes of vehicle components. Meanwhile, the CM-improved AHP is applied to assess risks for each basic event, reducing uncertainty from subjective data. Finally, we combine the technique for order preference by similarity to an ideal solution (TOPSIS) with the conversion function to provide quantitative probabilities for the top event and perform a sensitivity analysis of basic events. A case study on a real open-source test vehicle shows that the proposed method quantifies the probability of automatic emergency braking (AEB) system failure and ranks the risk for each basic event. Compared to existing methods, it has significant advantages in the comprehensiveness and objectivity of risk assessment, providing more accurate information for risk prevention.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110822"},"PeriodicalIF":9.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143219609","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-agent-based failure modeling for uncrewed swarm systems considering cross-layer diffusion characteristics","authors":"Xing Guo ,&nbsp;Qiang Feng ,&nbsp;Zeyu Wu ,&nbsp;Meng Liu ,&nbsp;Yi Ren ,&nbsp;Chao Yang ,&nbsp;Zili Wang","doi":"10.1016/j.ress.2025.110831","DOIUrl":"10.1016/j.ress.2025.110831","url":null,"abstract":"<div><div>Uncrewed swarm systems (USSs) are injecting renewed vigor into societal development and economic growth, and their failure modeling is crucial for ensuring the safety and stability of system operations. However, traditional modeling methods are insufficient for describing the cross-layer diffusion characteristics of USS failure. In this context, proposed here is a multi-agent-based failure modeling approach to establish the groundwork for analyzing USS failure. A failure modeling framework grounded in agent-based modeling methodology is developed to efficiently capture and organize the multi-layer failure information of a USS. Expanding on this framework, the interaction mechanism of agents is designed to delineate the operational processes and failure propagation paths of the USS. A dynamic clock failure model, structural functions, and functional constraint matrices are integrated effectively to describe the cross-layer failure behaviors of the components, subsystems, and nodes of the USS. Furthermore, a unified modeling approach is proposed to describe the failure propagation within and between nodes. Finally, a case study of a USS comprising 16 uncrewed aerial vehicles and eight satellites is conducted to validate the effectiveness of the proposed approach. The simulation results reveal that the electric distribution board, voltage stabilizer, and flight control board significantly influence the mission completion.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110831"},"PeriodicalIF":9.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143286320","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 systematic procedure for the analysis of maintenance reports based on a taxonomy and BERT attention mechanism","authors":"Dario Valcamonico ,&nbsp;Piero Baraldi ,&nbsp;July Bias Macêdo ,&nbsp;Márcio Das Chagas Moura ,&nbsp;Jonathan Brown ,&nbsp;Stéphane Gauthier ,&nbsp;Enrico Zio","doi":"10.1016/j.ress.2025.110834","DOIUrl":"10.1016/j.ress.2025.110834","url":null,"abstract":"<div><div>This work proposes a systematic procedure for analyzing maintenance reports to support maintenance decision-making for a fleet of similar systems. The proposed procedure allows achieving three objectives: (1) grouping maintenance interventions, (2) identifying common characteristics in the maintenance interventions, and (3) recognizing occurrences of rare events of maintenance intervention. Specifically, the attention mechanism of Bidirectional Encoder Representation from Transformer (BERT) and the Density Based Spatial Clustering Applications with Noise (DBSCAN) methods are combined to group maintenance interventions according to their similarity of stated features. A taxonomy of the words used in the textual reports to state the maintenance interventions is developed to systematically identify common features of the clusters, such as the involved components, their working state, the occurred failures or malfunctions, the performed maintenance actions and the personnel that has performed the intervention. The proposed procedure is applied to a repository of reports of maintenance interventions performed on mechanical and electric components of traction systems of a fleet of trains. The obtained results show that it can effectively support decision-making on the maintenance of traction systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110834"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143219608","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":"Enhancing reliability calculation for one-output k-out-of-n binary-state networks using a new BAT","authors":"Wei-Chang Yeh","doi":"10.1016/j.ress.2025.110835","DOIUrl":"10.1016/j.ress.2025.110835","url":null,"abstract":"<div><div>Evaluation of network reliability is a crucial aspect of system planning, design, and management. A k-out-of-n network is an important extension of the k-out-of-n system, which is a repairable redundancy binary-state system with <em>n</em> parallel components. The system fails if and only if at least k consecutive components fail, where k is an integer between 1 and <em>n</em>. In the proposed problem, at least k units of input flow are required to activate a node to output one unit of flow. This one-output <em>k-</em>out<em>-</em>of<em>-n</em> binary-state network model, along with a novel algorithm proposed to calculate its reliability, is motivated by real-life applications. The binary-addition-tree algorithm (BAT) can address this problem. By modifying the BAT and incorporating the novel cut-based layered-search method (CLSA), a novel algorithm is proposed to calculate the reliability of the proposed k-out-of-n binary-state network. The proposed algorithm is not limited to its original scope. The proposed algorithm has been extended to address additional scenarios. Specifically, it is now capable of solving traditional multi-output <em>k-</em>out<em>-</em>of<em>-n</em> networks. Based on both theoretical and empirical analyses conducted on examples, the proposed algorithm demonstrates greater efficiency and flexibility compared to the traditional BAT.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110835"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143286640","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":"Mathematical modeling of solar farm performance degradation in a dynamic environment for condition-based maintenance","authors":"Yaxin Shen ,&nbsp;Mitra Fouladirad ,&nbsp;Antoine Grall","doi":"10.1016/j.ress.2024.110778","DOIUrl":"10.1016/j.ress.2024.110778","url":null,"abstract":"<div><div>This paper aims to address the challenge of modeling and optimizing condition-based maintenance policies for a degraded solar farm in varying environmental conditions. Dust accumulation and temperature increases are the two main causes of performance reduction and energy loss in the system. In this research, dust accumulation is modeled by the non-homogeneous compound Poisson process, and three different mathematical models for the efficiency reduction of photovoltaic panels due to dust accumulation are considered. The effects of wind and rain, taken as covariates, on dust accumulation and temperature are investigated by stochastic process modeling. The covariate process is considered a time-homogeneous Markov chain with finite state space. The PV surface temperature is modeled by a non-homogeneous Markov chain with finite state space and transition matrices under covariate states. Different PV panels exhibit varied degradation rates, influenced by their position and tilt angle to sunlight. In the framework of the system, we derive multiple maintenance policies aimed at achieving the minimum cost criterion. The expected long-term average maintenance costs under different covariate conditions and maintenance policies are evaluated through simulation experiments to compare the effectiveness of each policy.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110778"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143218981","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":"Monitoring of operational resilience on urban road network: A Shaoxing case study","authors":"Jianwei Du ,&nbsp;Gang Ren ,&nbsp;Jialei Cui ,&nbsp;Qi Cao ,&nbsp;Jian Wang ,&nbsp;Chenyang Wu ,&nbsp;Jiefei Zhang","doi":"10.1016/j.ress.2025.110836","DOIUrl":"10.1016/j.ress.2025.110836","url":null,"abstract":"<div><div>Urban road networks (URNs), which are the critical infrastructure of a city, are fragile when faced with external disruptions. Efficient and accurate analyses of URN resilience of URNs could provide a new perspective for enhancing their ability to withstand, adapt, and recover from disruptive events. This study focused on the resilience evaluation and prediction of URN. A time-varying belief Markov-based resilience model was proposed to analyze the Operational Resilience (OR), which integrates link usability and driving efficiency. The OR is then converted to a normalized scale (COR), which is easier for decision-makers to understand. Finally, a case study was conducted to validate the proposed model. The results showed that demand, link capacity, disaster intensity, and road network structure are significant factors affecting the OR of a URN. Within the OR threshold, the recovery time is generally half the response time and is more stable among different links and precipitation intensities. It has been proven to have satisfactory performance in the estimation and prediction of resilience, which can capture the long-term OR of URN and identify key links and regions that require more attention. This approach could assist decision-makers in developing effective measures for disruptive events.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110836"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143219617","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":"Benchmark transformation neural network for health indicator construction under time-varying speed and its application in machinery prognostics","authors":"Jiahong Yang ,&nbsp;Jianghong Zhou ,&nbsp;Yi Chai ,&nbsp;Dingliang Chen ,&nbsp;Yi Qin","doi":"10.1016/j.ress.2025.110823","DOIUrl":"10.1016/j.ress.2025.110823","url":null,"abstract":"<div><div>A health indicator (HI) is usually applied to predict the remaining useful life (RUL) of machinery. The current HI construction methods typically only focus on constant operating conditions (such as speed or load), rendering them ineffective for variable-speed conditions. To address this gap, this paper proposes a HI construction method for machines under time-varying speed conditions based on benchmark transformation neural networks (BTNN). First, the baseline speed range is determined, and the baseline state observations are identified. Then, with the identified baseline observations, a performance degradation model is established via the double exponential function. Next, BTNN is innovatively proposed using the fitted degradation model, the monitoring state, and speed data to adaptively perform the complex nonlinear mapping from non-baseline observations to baseline values, avoiding the problem of selecting different baseline transformation functions. Compared with the HI constructed by a transformation function and the dimensionless HI, the proposed method unifies state observations at various speeds onto the baseline speed through BTNN, enhancing the comprehensive performance of HI. Comparative experiments on the RUL prediction of turbofan engines and wind turbine bearings reveal that the HI extracted by BTNN exhibits stronger prognosis capabilities than other classical and advanced HIs.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110823"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143286448","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":"Attack strategies and reliability analysis of Wireless Mesh Networks considering cascading failures","authors":"Hongyan Dui ,&nbsp;Jiabao Zhai ,&nbsp;Xiuwen Fu","doi":"10.1016/j.ress.2025.110832","DOIUrl":"10.1016/j.ress.2025.110832","url":null,"abstract":"<div><div>Wireless Mesh Networks (WMNs) are vital to modern infrastructure, and attacks on WMNs can lead to paralysis of interdependent systems, causing significant social and economic consequences. However, existing studies often assume all attacks coincide, focusing on cascading failures from a single perspective while neglecting specific attack strategies. This study is the first to apply sequential attack strategies to WMNs and conduct a comparative analysis with synchronous strategies. First, we propose a system model for WMNs that incorporates path loss and link capacity, representing real-world scenarios. Secondly, we introduce two novel reliability metrics, transmission reliability and reliability degradation rate, to quantify the impact of attacks. In the final case study, we analyze the effects of synchronous and sequential attack strategies under four node attack rules. Results reveal that sequential attack strategies dynamically identify and exploit critical nodes, causing prolonged degradation of transmission reliability and amplifying cascading failures. Compared to synchronous attack strategies, sequential attack strategies increase the global reliability degradation rate and reliability degradation rate during the attack phase by 28.62 % and 55.36 %, respectively. Therefore, sequential attack strategies should combine these two node attack rules to achieve maximum impact. These findings confirm that the proposed sequential attack strategy effectively disrupts network performance and provides meaningful insights for developing WMN defense strategies.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"257 ","pages":"Article 110832"},"PeriodicalIF":9.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143286635","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}