Reliability Engineering & System Safety最新文献_第4页

A reliability evaluation method for multi-state flow networks considering network configuration adjustment 考虑网络配置调整的多状态流网络可靠性评估方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-15 DOI: 10.1016/j.ress.2025.111158

Tao Liu , Jun Liu , Guanghan Bai , Junfu Zhang , Libo Wang

{"title":"A reliability evaluation method for multi-state flow networks considering network configuration adjustment","authors":"Tao Liu , Jun Liu , Guanghan Bai , Junfu Zhang , Libo Wang","doi":"10.1016/j.ress.2025.111158","DOIUrl":"10.1016/j.ress.2025.111158","url":null,"abstract":"<div><div>Reliability serves as a critical metric for assessing the performance of multi-state flow networks (MFNs). During the processes of designing, optimizing, or conducting resilience analysis on these networks, the configuration of the network might undergo changes. Consequently, the reliability evaluation process may need to be iterated multiple times to identify an acceptable network configuration in these scenarios. However, due to the inherent NP-hard complexity of reliability assessment in MFNs, repeated evaluations can lead to high computational costs. To address this challenge, we propose a comprehensive MFN reliability evaluation framework that enhances both efficiency and accuracy when network configurations adjust. This framework integrates three key methods, each designed for different scenarios. An improved state space decomposition (SSD) method, and a deeper SSD method are proposed to obtain the sets of state space of a MFN that can ensure the preset accuracy demand. Besides, we developed a state space reconstruction (SSR) method to update the sets of state space when network configuration changes. These methods work collaboratively within the framework to reduce computational costs while ensuring reliable assessments. Performance evaluations demonstrate that the proposed framework significantly improves computational efficiency and maintains high result accuracy, making it suitable for iterative MFN reliability assessments.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111158"},"PeriodicalIF":9.4,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863587","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

Interpretability study of a typical fault diagnosis model for nuclear power plant primary circuit based on a graph neural network 基于图神经网络的核电站一次电路典型故障诊断模型的可解释性研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-13 DOI: 10.1016/j.ress.2025.111151

Xin Wang, Hang Wang, MinJun Peng

{"title":"Interpretability study of a typical fault diagnosis model for nuclear power plant primary circuit based on a graph neural network","authors":"Xin Wang, Hang Wang, MinJun Peng","doi":"10.1016/j.ress.2025.111151","DOIUrl":"10.1016/j.ress.2025.111151","url":null,"abstract":"<div><div>Weak interpretability has become a huge obstacle for the practical application of artificial intelligence diagnosis models in the nuclear field. In order to solve the above problem, this study proposes a fault diagnosis method of Graph Neural Networks (GNNs) combined with fault causal directed graph. The method summarizes the typical fault causal directed graphs of nuclear power plant through the system physical structure and expert knowledge, and combines it with the spatial inductive framework of GNNs to achieve qualitative interpretable diagnosis. Furthermore, this study analyses the feature representation weights of various types of sensor nodes in the fault diagnosis process based on the self-attention mechanism, which is used to elucidate the decision-making process of the model's fault diagnosis and to achieve quantitative interpretability analysis. The proposed model is validated by simulation data from the simulator of Fuqing No.1 pressurised water reactor nuclear power plant. The results show that the proposed model is able to diagnose the fault types effectively, and the decision-making process of the model is logical and interpretable. Therefore, this study opens up a new technical approach with both accuracy and interpretability in the field of nuclear power plant fault diagnosis. By improving the interpretability of the intelligent diagnosis model, it effectively promotes the application of artificial intelligence technology in the fault diagnosis field of the nuclear industry, and provides a new enlightenment for the application of complex system fault diagnosis in other fields.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111151"},"PeriodicalIF":9.4,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848505","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

Quantum Fault Trees and Minimal Cut Sets Identification 量子故障树与最小割集辨识

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-12 DOI: 10.1016/j.ress.2025.111147

Gabriel San Martín Silva , Enrique López Droguett

{"title":"Quantum Fault Trees and Minimal Cut Sets Identification","authors":"Gabriel San Martín Silva , Enrique López Droguett","doi":"10.1016/j.ress.2025.111147","DOIUrl":"10.1016/j.ress.2025.111147","url":null,"abstract":"<div><div>Fault Trees represent an essential tool in the reliability and risk assessment of complex engineering systems. One of the core tasks in Fault Tree analysis is the identification of Minimal Cut Sets, defined as groups of components that present the least path of resistance toward a system's failure. Nonetheless, minimal cut set identification remains a highly challenging problem due to the exponential growth in feasible configurations as the system size increases linearly. Recently, quantum computation has been heralded as a promising tool to tackle computational challenges of increased complexity. However, its integration into reliability engineering, and in particular to challenges related to Fault Tree modeling, is still underexplored. To fill this relevant gap, this paper integrates quantum computation into the Fault Tree Model to assess its capabilities for minimal cut set identification. To this end, this paper proposes a novel approach to encode a fault tree into a quantum algorithm and perform the identification of minimal cut sets via the application of the Grover operator. For validation purposes, a series of theoretical and numerical results, the latter obtained using a quantum simulator, are presented in which the proposed algorithm is compared against a state-of-the-art non-quantum approach.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111147"},"PeriodicalIF":9.4,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882947","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 dynamic risk-informed framework for emergency human error prevention in high-risk industries: A Nuclear Power Plant case study 在高风险工业中预防紧急人为错误的动态风险知情框架：一个核电站案例研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-11 DOI: 10.1016/j.ress.2025.111080

Xingyu Xiao , Ben Qi , Shunshun Liu , Peng Chen , Jingang Liang , Jiejuan Tong , Haitao Wang

{"title":"A dynamic risk-informed framework for emergency human error prevention in high-risk industries: A Nuclear Power Plant case study","authors":"Xingyu Xiao , Ben Qi , Shunshun Liu , Peng Chen , Jingang Liang , Jiejuan Tong , Haitao Wang","doi":"10.1016/j.ress.2025.111080","DOIUrl":"10.1016/j.ress.2025.111080","url":null,"abstract":"<div><div>Human reliability analysis (HRA) plays a pivotal role in safety-critical systems, with its methodological evolution currently advancing into the third generation, characterized by dynamic modeling and deeper cognitive processing frameworks. In this study, we propose a novel paradigm extension to HRA, introduced within an emergent operational environment. Specifically, we develop a dynamic risk-informed framework (DRIF) that integrates Bayesian networks (BNs), long short-term memory (LSTM) neural networks, and domain-specific emergency operating procedures (EOPs) to enable real-time evaluation of human error risks during emergency scenarios. The framework employs Bayesian networks to probabilistically model causal relationships among human factors, while LSTM networks dynamically process temporal operational data streams for fault diagnosis. This hybrid architecture synergizes HRA principles with real-time risk propagation mechanisms, thereby enhancing situational awareness and decision granularity under time-critical conditions. To empirically validate DRIF’s efficacy, we implemented it in anomaly mission scenarios for a high-temperature gas-cooled reactor (HTGR). The case study demonstrates the framework’s capability to (1) quantify human error probabilities (HEPs) through probabilistic inference, (2) identify latent risk pathways via backward propagation analysis, and (3) provide prescriptive guidance aligned with EOPs for risk mitigation. The results show that the more precisely later emergency action measures are implemented, the better the accident prevention and control effect during emergencies. This advancement establishes a methodological foundation for next-generation HRA systems in complex engineered systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111080"},"PeriodicalIF":9.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828798","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

Optimizing community post-earthquake emergency medical capability via mobile hospital configuration 通过移动医院配置优化社区震后应急医疗能力

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-11 DOI: 10.1016/j.ress.2025.111133

Taiyi Zhao , Cong Zeng , Cunjie Chu , Yuchun Tang , Jingquan Wang

{"title":"Optimizing community post-earthquake emergency medical capability via mobile hospital configuration","authors":"Taiyi Zhao , Cong Zeng , Cunjie Chu , Yuchun Tang , Jingquan Wang","doi":"10.1016/j.ress.2025.111133","DOIUrl":"10.1016/j.ress.2025.111133","url":null,"abstract":"<div><div>Emergency medical capability is critical for communities to reduce casualties after earthquakes. In this research, a bi-level design optimization model for the configuration of mobile hospitals is developed to minimize both the post-earthquake transfer time of casualties from their residential areas to the mobile hospitals, and the within-hospital service time including mean queue waiting time and average processing time. The upper level of the model characterizes community officials’ decisions regarding possible mobile hospital configuration that consists of three decision variables: the location of mobile hospitals on candidate sites, their functional classes, and the number of attending physicians dispatched to them. The lower level model leverages the mixed user equilibrium traffic assignment to simulate the path selection behaviour of drivers transferring casualties with different injury heterogeneity under different information perceptions. Meanwhile, considering the uncertainty in the number of casualties and the post-earthquake damage state of bridges, a robust configuration model for the stochastic case is also established based on the robust optimization theory. To tackle the optimization model, an interactive solution approach combining the genetic algorithm and the modified mixed equilibrium assignment algorithm is presented. A demonstrative study is conducted on a middle-class city located in an earthquake-prone area.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111133"},"PeriodicalIF":9.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844747","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

Modeling and analysis of open-pit coal mine accident causation based on directed weighted network 基于有向加权网络的露天煤矿事故成因建模与分析

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-11 DOI: 10.1016/j.ress.2025.111141

Yuanzhen Li , Yunlei She , Ying Shi , Rijia Ding

{"title":"Modeling and analysis of open-pit coal mine accident causation based on directed weighted network","authors":"Yuanzhen Li , Yunlei She , Ying Shi , Rijia Ding","doi":"10.1016/j.ress.2025.111141","DOIUrl":"10.1016/j.ress.2025.111141","url":null,"abstract":"<div><div>Open-pit coal mining is a complex process with a broad operational scope, increasing the risk of accidents and posing management challenges. This study presents a directed weighted network modeling approach based on accident cases. The approach integrates grounded theory, event chain analysis, and complex network theory to construct the open-pit coal mine accident causation network (OPCMACN). The OPCMACN encompasses causal nodes across five dimensions: human, equipment, environment, management, and technology, along with accident nodes, illustrating their complex interconnections. A topological analysis framework suitable for directed weighted networks is proposed to analyze the structure of the OPCMACN. By considering four dimensions: node neighbors, path hubs, random walks, and positional information, topological metrics suitable for directed weighted networks are used to identify key causal factors, enabling the recommendation of targeted preventive measures. Furthermore, a comprehensive accident causation governance approach (CACGA) is introduced, integrating the advantages of various topological metrics across different stages of causal factor governance. The robustness analysis reveals significant vulnerabilities in the OPCMACN when key nodes are governed while confirming the superiority of CACGA throughout the entire governance process. The research findings provide essential theoretical support for decision-making in managing the safety of open-pit coal mines and offer a comprehensive, novel perspective for accident analysis in other system safety fields.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111141"},"PeriodicalIF":9.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855728","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

Dynamic enterprise resilience assessment for port systems: A framework integrating Bayesian networks and Dempster-Shafer evidence theory 港口系统动态企业弹性评估：一个整合贝叶斯网络和Dempster-Shafer证据理论的框架

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-11 DOI: 10.1016/j.ress.2025.111105

Nanxi Wang, Min Wu, Kum Fai Yuen

{"title":"Dynamic enterprise resilience assessment for port systems: A framework integrating Bayesian networks and Dempster-Shafer evidence theory","authors":"Nanxi Wang, Min Wu, Kum Fai Yuen","doi":"10.1016/j.ress.2025.111105","DOIUrl":"10.1016/j.ress.2025.111105","url":null,"abstract":"<div><div>Ports act as vital nodes in the global transportation network, facilitating 80 % of international trade and supporting economic development. Despite their importance, port enterprises face growing vulnerabilities to global disruptions. Enterprise resilience (ER) is a critical capability that enables these dynamic and complex systems to address such challenges. This study develops a comprehensive framework for dynamically assessing ER, addressing the urgent need for enhanced resilience in port enterprises. The proposed framework integrates Dynamic Bayesian Networks (DBNs) with the Dempster-Shafer evidence interval theory, enabling the incorporation of both objective data and subjective expert judgments while managing uncertainty and conflict. Two time-evolution resilience models are introduced, encompassing multidimensional factors across economic, environmental, social, and technological domains. Case studies involving four major Chinese port enterprises—Shanghai, Ningbo Zhoushan, Tianjin, and Guangzhou Port—illustrate the framework's applicability. The analysis reveals varying temporal patterns in ER, identifies critical factors such as technological innovation and learning capabilities, and highlights the dynamic nature of resilience. This research contributes to ER theory by emphasizing the significance of learning capabilities in the dynamic adaptation of systems. It offers a novel approach to resilience research and management, providing a transferable framework for decision-makers in maritime transportation and other complex systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111105"},"PeriodicalIF":9.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879035","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

Physics informed neural networks for detecting the wear of friction pairs in axial piston pumps 基于物理信息的神经网络检测轴向柱塞泵摩擦副磨损

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-11 DOI: 10.1016/j.ress.2025.111144

Qun Chao , Yong Hu , Chengliang Liu

{"title":"Physics informed neural networks for detecting the wear of friction pairs in axial piston pumps","authors":"Qun Chao , Yong Hu , Chengliang Liu","doi":"10.1016/j.ress.2025.111144","DOIUrl":"10.1016/j.ress.2025.111144","url":null,"abstract":"<div><div>The wear of friction pairs is one of the most common failure mechanisms for axial piston pumps and its accurate detection is essential for ensuring safety and reliability of hydraulic systems. The existing studies on the wear detection of friction pairs in axial piston pumps is focused on data-driven fault diagnosis models, but these black-box data-driven models are limited by poor interpretability and physical inconsistency. To overcome this limitation, this paper proposes an interpretable wear detection method for the friction pairs of axial piston pumps based on physics informed neural networks. First, we establish an ordinary differential equation (ODE) for the time derivative of discharge pressure to relate the instantaneous discharge pressure with the fluid film thicknesses in friction pairs that represent the wear condition of axial piston pumps. Second, we develop a physics informed neural network and a multi-parameter dynamic identification method to identify the fluid film thickness in each friction pair by inversely solving the ODE based on observed discharge pressure signals. Finally, we propose an interpretable wear detection method based on the pump's volumetric efficiency and effect size of fluid film thickness. Experimental results suggest that the identification results of fluid film thickness in the friction pairs have a good physical consistency, and the proposed method can locate the worn friction pair with a high model interpretability.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111144"},"PeriodicalIF":9.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834958","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

PDET-based assumption-free method for efficient seismic fragility assessment of slopes with combined uncertainties of soil materials and input ground motions 基于pdt的边坡地震易损性综合评价方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-10 DOI: 10.1016/j.ress.2025.111132

Hongqiang Hu , Yangjuan Bao , Yu Huang , Min Xiong , Wenwen Wang

{"title":"PDET-based assumption-free method for efficient seismic fragility assessment of slopes with combined uncertainties of soil materials and input ground motions","authors":"Hongqiang Hu , Yangjuan Bao , Yu Huang , Min Xiong , Wenwen Wang","doi":"10.1016/j.ress.2025.111132","DOIUrl":"10.1016/j.ress.2025.111132","url":null,"abstract":"<div><div>Seismic fragility denotes the probabilities of a system exceeding some prescribed damage levels under a range of seismic intensities. Classical seismic fragility studies in slope engineering usually construct fragility functions by making some assumptions for fragility curve shape, and always neglect spatial variability of soil materials. In this study, an assumption-free method on the basis of probability density evolution theory (PDET) is proposed for seismic fragility assessment of slopes. The random input earthquakes and spatially-variable soil parameters in slope are simultaneously quantified. By the proposed method, assumption-free fragility curves of a slope are established without limiting the fragility curve shape. The obtained fragility results are also compared with those from two classic parametric fragility methods (linear regression and maximum likelihood estimation) and Monte Carlo simulation. The results demonstrate that the proposed assumption-free method has potential to gives more rigorous and accurate fragility results than classical parametric fragility analysis methods. With the proposed method, more reliable fragility results can be obtained for slope seismic risk assessment.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111132"},"PeriodicalIF":9.4,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848504","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

Intelligent diagnosis method for early faults of electric-hydraulic control system based on residual analysis 基于残差分析的电液控制系统早期故障智能诊断方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-04-10 DOI: 10.1016/j.ress.2025.111142

Xiangdi Kong , Baoping Cai , Yulong Yu , Jun Yang , Bo Wang , Zijie Liu , Xiaoyan Shao , Chao Yang

{"title":"Intelligent diagnosis method for early faults of electric-hydraulic control system based on residual analysis","authors":"Xiangdi Kong , Baoping Cai , Yulong Yu , Jun Yang , Bo Wang , Zijie Liu , Xiaoyan Shao , Chao Yang","doi":"10.1016/j.ress.2025.111142","DOIUrl":"10.1016/j.ress.2025.111142","url":null,"abstract":"<div><div>Early faults typically manifest as subtle changes on signals owing to its significant concealment and inherent randomness. The diagnosis of early fault holds significant importance for enhancing operational safety and production efficiency. To address the challenge of weak features and often high uncertainty associated with early fault characteristics, this study proposed an early fault diagnosis method for electric-hydraulic control system with features obtained by residual analysis. The residual features are extracted and analyses through residual signal extraction, residual processing, feature extraction, and residual feature sensitivity assessment. The new features obtained are applied to optimize the fault diagnostic model established based on Bayesian network. The incentive factor evaluation model based on residual feature analysis and the fault diagnosis result correction mechanism based on Bayesian network model are then established. The newly developed method is applied to a control system for subsea blowout preventer used as a case study to analyse the early fault evolution mechanism.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"261 ","pages":"Article 111142"},"PeriodicalIF":9.4,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838575","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