Reliability Engineering & System Safety最新文献_第6页

Time-dependent system reliability analysis of a high concrete-faced rockfill dam by integrating multi-source monitoring information 综合多源监测信息的高面板堆石坝系统时变可靠性分析

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-16 DOI: 10.1016/j.ress.2025.111251

Ming Peng , Longhou Gan , Qiming Zhong , Ge Yang , Gang Deng , Zijun Cao , Zhenming Shi

{"title":"Time-dependent system reliability analysis of a high concrete-faced rockfill dam by integrating multi-source monitoring information","authors":"Ming Peng , Longhou Gan , Qiming Zhong , Ge Yang , Gang Deng , Zijun Cao , Zhenming Shi","doi":"10.1016/j.ress.2025.111251","DOIUrl":"10.1016/j.ress.2025.111251","url":null,"abstract":"<div><div>This paper presents a time-dependent reliability analysis method for concrete-faced rockfill dams (CFRDs) by integrating multiple failure modes and multi-source monitoring data via Bayesian networks. Initially, two sub-Bayesian networks are constructed to fuse dam parameters, two related failure modes, and three types of monitoring data. Subsequently, the prior failure probabilities of the dam system for each period are calculated through the time-variant response relationships among network nodes. These response relationships introduce a time-variant term to quantify the effects of water level and creep. Finally, various types of monitoring data are utilized to update parameter distribution, resulting in the posterior failure probabilities. The proposed method is applied to 233-meter-high Shuibuya CFRD. The results indicate that Bayesian networks offer a more comprehensive and reliable assessment. Water level induces periodic variations in system reliability, while creep drives the long-term trend by increasing slabs' failure probabilities. The failure probabilities of dam system increase over the initial ten years and stabilize as creep converges. The slabs’ failure probabilities vary from location. Seepage failure probability is primarily dominated by the most critical slab. Utilizing multi-source monitoring data can reduce uncertainties, mitigate the interference of localized abnormal data, and identify potential failure locations. This approach supports enhanced dam safety management.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111251"},"PeriodicalIF":9.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106937","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

Traffic function damage risk assessment of high-speed railway simply-supported bridges considering the total probability information expression of near-fault pulse-like earthquakes 考虑近断层脉状地震全概率信息表达的高速铁路简支桥交通功能损伤风险评估

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-15 DOI: 10.1016/j.ress.2025.111241

Gaoyang Zhou , Zhihui Zhu , Weiqi Zheng , Kun Wang

{"title":"Traffic function damage risk assessment of high-speed railway simply-supported bridges considering the total probability information expression of near-fault pulse-like earthquakes","authors":"Gaoyang Zhou , Zhihui Zhu , Weiqi Zheng , Kun Wang","doi":"10.1016/j.ress.2025.111241","DOIUrl":"10.1016/j.ress.2025.111241","url":null,"abstract":"<div><div>As a critical lifeline project in high seismic intensity regions, the high-speed railway (HSR) system unavoidably involves numerous bridges located near active faults, making them highly susceptible to the threat of near-fault pulse-like (NFPL) earthquakes. This study proposes a method for assessing the traffic function damage risk of high-speed railway simply supported beam bridges (HSRSSBs), considering the total probability information of NFPL earthquakes. Focused on the post-earthquake traffic function of bridges, the method defines a comprehensive evaluation system for the function damage of HSRSSBs. Utilizing a probability model for NFPL earthquakes, an analysis function for the function vulnerability of railway bridges is proposed, considering the probabilities of earthquake occurrence, pulse period, and pulse direction. The effects of different NFPL earthquake parameters on the function damage probability of HSRSSB are analyzed. Finally, combined with the probabilistic seismic hazard analysis (PSHA) method, the study investigates the function damage risk of HSRSSBs under various site conditions and seismic risk levels. This method comprehensively considers the probability distribution of NFPL earthquakes resulting from the spatial characteristics of bridges and fault, providing valuable insights for the seismic damage risk assessment of HSR bridges in active fault regions.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111241"},"PeriodicalIF":9.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084581","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

Uncertainty quantification and source identification of critical safety parameters in CiADS via sensitivity analysis 基于灵敏度分析的CiADS关键安全参数不确定度定量及来源识别

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-15 DOI: 10.1016/j.ress.2025.111259

Chao Yang , Chun-Feng Hu , Lili Wen , Zhen-Ping Chen , Tao Yu

{"title":"Uncertainty quantification and source identification of critical safety parameters in CiADS via sensitivity analysis","authors":"Chao Yang , Chun-Feng Hu , Lili Wen , Zhen-Ping Chen , Tao Yu","doi":"10.1016/j.ress.2025.111259","DOIUrl":"10.1016/j.ress.2025.111259","url":null,"abstract":"<div><div>The safe disposal of nuclear waste is a major problem for sustainable development of fission nuclear energy. Accelerator driven subcritical systems (ADS) have excessive high-energy spallation neutrons, and are the preferred technological approach for transmutation of nuclear waste. ADS has the characteristics of wide neutron energy distribution range and complex nuclear fuel composition, which creates significant uncertainty in safety analysis and affects the reliability of safety parameter calculation results. An uncertainty quantification methodology for safety parameter is proposed based on the adjoint weighted perturbation theory, and an uncertainty analysis program MCSU is developed. Using a comprehensive nuclear data covariance library that is established in this paper, the uncertainties of important safety parameters of China Initiative Accelerator Driven System (CiADS) are quantified. Furthermore, an energy-dependent uncertainty contribution factor method is employed to identify isotopes, cross-sections, and energy ranges contributing most significantly to the overall uncertainty. The results demonstrated that uncertainties caused by nuclear data far exceed the accuracy limit requirements of advanced nuclear systems, the accuracy of nuclear data needs to be improved, especially in the high-energy region, the research results provide guidance for improving the reliability of safety parameters.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111259"},"PeriodicalIF":9.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089070","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

Hierarchical importance sampling method for estimating failure probability function 失效概率函数估计的分层重要性抽样方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-15 DOI: 10.1016/j.ress.2025.111258

Yizhou Chen , Zhenzhou Lu , Xinglin Li

{"title":"Hierarchical importance sampling method for estimating failure probability function","authors":"Yizhou Chen , Zhenzhou Lu , Xinglin Li","doi":"10.1016/j.ress.2025.111258","DOIUrl":"10.1016/j.ress.2025.111258","url":null,"abstract":"<div><div>Failure probability function can quantify the structural safety levels when the random input distribution parameter varies within the concerned design region, and it can decouple the reliability-based design optimization model. To efficiently estimate it, a hierarchical importance sampling method is proposed. The main contributions of this paper are threefold. The first is constructing a novel single-loop optimal importance sampling density, on which the double-loop framework of analyzing the failure probability function is decoupled. The second is employing Markov Chain Monte Carlo simulation to extract the samples of the single-loop optimal importance sampling density in an adaptively hierarchical way. Compared to the existing single-loop cross-entropy based importance sampling method, the proposed method eliminates iterative determination of the unknown parameter set of the Gaussian mixture model. The third is utilizing a Gaussian mixture model to inversely approximate the single-loop optimal importance sampling density, enabling efficient and accurate estimation of the failure probability function. By integrating the single-loop strategy, importance sampling variance reduction technique, and inverse approximation of Gaussian mixture model, the proposed method improves the efficiency of estimating failure probability function while maintaining the accuracy, which is rigorously validated through five examples, demonstrating the superior performance compared to state-of-the-art alternatives.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111258"},"PeriodicalIF":9.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098844","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

Analyzing the dynamic domino effect in fuel truck parking lots 油罐车停车场动态多米诺效应分析

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-15 DOI: 10.1016/j.ress.2025.111256

Kamran Gholamizadeh , Esmaeil Zarei , Ahmad BahooToroody

{"title":"Analyzing the dynamic domino effect in fuel truck parking lots","authors":"Kamran Gholamizadeh , Esmaeil Zarei , Ahmad BahooToroody","doi":"10.1016/j.ress.2025.111256","DOIUrl":"10.1016/j.ress.2025.111256","url":null,"abstract":"<div><div>Fuel truck parking lots are crucial components of transportation networks, facilitating the storage and organization of fuel trucks to ensure efficient fuel distribution. These facilities play a vital role in minimizing transportation delays and reducing emissions. However, the proximity of fuel tanks in these lots poses inherent risks, including fire, explosions, and domino accidents. The present study aimed to analyze the domino effect in fuel truck parking lots. To achieve this, a hybrid approach combining the Dempster-Shafer Theory (DST) method with the Bayesian networks (BNs) was employed for quantitative cause-consequence analysis. Additionally, empirical equations were utilized to model the consequences, followed by the dynamic analysis of the domino effect using the Multi-Agent (MA) method. The accuracy of the introduced hybrid method was evaluated through a case study conducted at one of the most sizable parking lots. The study demonstrated the effectiveness of proposed approach in quantifying risks and identifying mitigation strategies, highlighting its applicability in real-world scenarios. Moreover, the proposed hybrid model offers a scientifically rigorous framework for handling uncertainty, providing valuable insights for enhancing safety measures and mitigating risks in fuel truck parking lots.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111256"},"PeriodicalIF":9.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106938","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

Preferred decision for industrial equipment operation rotation considering health state based on belief rule base and evidential reasoning 基于信念规则库和证据推理的考虑健康状态的工业设备运行轮换优选决策

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-15 DOI: 10.1016/j.ress.2025.111264

Zheng Lian, Zhi-Chao Feng, Zhi-Jie Zhou, Chang-Hua Hu, Lai-Hong Hu, Fu-Qiao Zhang

{"title":"Preferred decision for industrial equipment operation rotation considering health state based on belief rule base and evidential reasoning","authors":"Zheng Lian, Zhi-Chao Feng, Zhi-Jie Zhou, Chang-Hua Hu, Lai-Hong Hu, Fu-Qiao Zhang","doi":"10.1016/j.ress.2025.111264","DOIUrl":"10.1016/j.ress.2025.111264","url":null,"abstract":"<div><div>The health state of equipment will decline in the long-term operation, resulting in the need to rotate multiple equipment to fulfill the operation task (OT). In the current engineering, three available equipment rotation strategies are summarized. However, the selection of these strategies is arbitrary and the health state of the equipment during operation rotation is neglected, which causes poor benefits and heavy risks. For this purpose, a quantitative decision-making mechanism using belief rule base (BRB) and evidential reasoning (ER) is proposed to determine the preferred strategy. Specifically, BRB serves as the preferred decision model, which reflects the mapping relationship between the OT and the rotation strategy. A parameter optimization model is then designed to improve decision rationality. To obtain the labeled historical OTs required for the parameter optimization model, a hierarchical ER method is developed to evaluate the performance of the rotation strategy to obtain the labeled historical OTs, where the health state of the equipment is quantitatively analyzed. The proposed method comprehensively utilizes knowledge and data and provides a quantitative decision-making framework for equipment operation rotation. A case of the natural gas storage tank (NGST) verifies the effectiveness of the proposed method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"263 ","pages":"Article 111264"},"PeriodicalIF":9.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135221","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

Fouling-characteristic transfer learning for improving remaining useful lifetime prediction in heat exchange unit 污垢特征迁移学习改进换热装置剩余使用寿命预测

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-14 DOI: 10.1016/j.ress.2025.111250

Santi Bardeeniz , Chanin Panjapornpon , Patamawadee Chomchai , Mohamed Azlan Hussain

{"title":"Fouling-characteristic transfer learning for improving remaining useful lifetime prediction in heat exchange unit","authors":"Santi Bardeeniz , Chanin Panjapornpon , Patamawadee Chomchai , Mohamed Azlan Hussain","doi":"10.1016/j.ress.2025.111250","DOIUrl":"10.1016/j.ress.2025.111250","url":null,"abstract":"<div><div>Accurately predicting the remaining useful lifetime (RUL) of heat transfer units is essential for optimizing maintenance schedules and ensuring efficient operation in industrial processes. Traditional models often struggle with varying components, operating conditions, and limited training datasets, while none have explored how fouling behavior can be shared across different fluid characteristics. The current study introduced a fouling factor transfer learning-based long short-term memory model, which utilized pre-trained fouling factor representation from crude oil to improve RUL predictions for its derivatives, such as asphaltene and olefin, and extended the approach to other fluids, such as glycerin, across different unit operations. The proposed model achieved notable improvements, with RUL prediction accuracy reaching up to 99.6% for asphaltene and 96.8% for olefin, while maintaining robust performance for glycerin (despite domain discrepancies), with an average prediction error of 7 days in glycerin case study. In addition, the model was computationally efficient, reducing training time by 50% for asphaltene and olefin and by 9% for crude oil, underscoring its adaptability. By applying shared fouling dynamics across different fluids, the proposed model effectively addresses challenges related to limited data availability, enhances generalization across chemical processes, and offers a more reliable and efficient tool for predictive maintenance strategies in petrochemical industries.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111250"},"PeriodicalIF":9.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089071","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

Resilience-based importance measure for ultra-high voltage converter stations under mainshock-aftershock sequences 主余震序列下超高压换流站的弹性重要性度量

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-14 DOI: 10.1016/j.ress.2025.111245

Zhihang Xue , Kai Wang , Di Cao , Siyu Zhou , Yu Liu

{"title":"Resilience-based importance measure for ultra-high voltage converter stations under mainshock-aftershock sequences","authors":"Zhihang Xue , Kai Wang , Di Cao , Siyu Zhou , Yu Liu","doi":"10.1016/j.ress.2025.111245","DOIUrl":"10.1016/j.ress.2025.111245","url":null,"abstract":"<div><div>Ultra-high voltage (UHV) converter stations are crucial for power systems, but their towering structures are highly vulnerable to earthquakes. It is, therefore, of great significance to enhance the resilience of the converter stations such that they can withstand and recover promptly from disruptions caused by earthquakes. Nevertheless, the uncertainties associated with earthquakes significantly hinder the post-earthquake recovery process, thus impacting importance ranking of the equipment in UHV converter stations. To address these uncertainties, this article proposes a new resilience-based importance (RBI) measure integrating vulnerability and recoverability under mainshock-aftershock sequences. Specifically, a roulette-wheel damage scenario generation method is adopted to generate equipment damage scenarios considering uncertainties. RBI measures considering cumulative damage effects from mainshock-aftershock sequences are calculated to evaluate equipment vulnerability and recoverability. The Copeland Score (CS) stochastic ranking method ranks equipment RBI, providing an optimal prioritization strategy for post-earthquake recovery. A case study of a ± 800 kV converter station demonstrates the proposed RBI method. Results show the RBI-based recovery strategy improves resilience by 10.4 % compared to traditional performance recovery importance (PRI) method. Neglecting aftershocks would result in approximately a 5.6 % overestimation of resilience.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111245"},"PeriodicalIF":9.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084580","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

Continual multi-target domain adaptation for industrial process fault diagnosis 面向工业过程故障诊断的连续多目标域自适应

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-14 DOI: 10.1016/j.ress.2025.111239

Shijin Li, Xufei Chen, Huizhi Zhang, Jianbo Yu

{"title":"Continual multi-target domain adaptation for industrial process fault diagnosis","authors":"Shijin Li, Xufei Chen, Huizhi Zhang, Jianbo Yu","doi":"10.1016/j.ress.2025.111239","DOIUrl":"10.1016/j.ress.2025.111239","url":null,"abstract":"<div><div>In multi-operating condition production processes, process data typically arrive continuously with distinct distribution. Domain adaptation techniques are commonly employed to settle the domain shift caused by variations in operating conditions. However, those models trained on continual data streams face the dilemma of adapting to new data while forgetting old knowledge. In this study, a novel transfer learning model called continual multi-target domain adaptation with dual knowledge distillation (CMTDA-DKD) is proposed for process fault diagnosis, which is trained on multiple target domains collected sequentially from varying working conditions. To adapt to the target streams from different working conditions, maximum mean discrepancy and adversarial training are utilized to narrow the distribution gap and guide the feature generator to learn domain invariant features between source and target domains. In addition, a dual knowledge distillation module is proposed to mitigate catastrophic forgetting of previous target domains in both feature and class levels. Moreover, a knowledge bank based on a sample selection module is proposed to restore the representative target domain samples in previous incremental stages, which enables the model to preserve prior knowledge. The application performance of CMTDA-DKD in continuous stirred tank reactor process, three-phase process and a hydraulic system demonstrates its effectiveness and superiority over other methods.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111239"},"PeriodicalIF":9.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089068","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

Analyzing factors influencing defect-based conditions for sewer pipes using Bayesian networks 利用贝叶斯网络分析污水管道缺陷状态的影响因素

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-05-14 DOI: 10.1016/j.ress.2025.111243

Shihui Ma , Tarek Zayed , Jiduo Xing , Zhihao Ren

{"title":"Analyzing factors influencing defect-based conditions for sewer pipes using Bayesian networks","authors":"Shihui Ma , Tarek Zayed , Jiduo Xing , Zhihao Ren","doi":"10.1016/j.ress.2025.111243","DOIUrl":"10.1016/j.ress.2025.111243","url":null,"abstract":"<div><div>The failure and condition of sewer pipes are usually influenced by various uncertainties and factors. Therefore, it is vital to evaluate the defect-based condition of sewer pipes for maintenance and failure prevention. In contrast to relying on the existing domain knowledge, this paper proposes a data-driven Bayesian network (BN) model to analyze the impacts of different influence factors (IFs) on the sewer pipes’ defect-based condition based on the developed database about the Hong Kong sewer network. Specifically, fourteen IFs are collected to develop a multi-source integrated database that incorporates pipe physical, environment, and climate-related factors. Then, the structure of the BN model is learned by Bayesian searching algorithm, and the reliability of the proposed model is evaluated using sensitivity analysis methods. Moreover, special scenarios are assumed to explore possible configurations of IFs. The results reveal that age, diameter, population and soil type are the top four IFs affecting the condition of sewer pipes, among which pipes with some characteristics need to be closely monitored, such as pipe age greater than 50 years, diameter less than 200 mm, location with a population density less than 15,000, and location in fill or granitic rocks. This paper improves sewer pipe management by integrating a comprehensive database and enabling reliable pipe condition inferences. The insights provide practical suggestions for the sewer pipe layout, risk analysis, and maintenance strategy formulation. It is a precious tool for authorities to enhance the safety and efficiency of sewer system management.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"262 ","pages":"Article 111243"},"PeriodicalIF":9.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089069","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