Marco Behrendt , Vasileios C. Fragkoulis , George D. Pasparakis , Michael Beer
{"title":"Probabilistic failure analysis of stochastically excited nonlinear structural systems with fractional derivative elements","authors":"Marco Behrendt , Vasileios C. Fragkoulis , George D. Pasparakis , Michael Beer","doi":"10.1016/j.ress.2025.111647","DOIUrl":"10.1016/j.ress.2025.111647","url":null,"abstract":"<div><div>In this paper, the application of the relaxed power spectral density (PSD) framework is developed for quantifying uncertainties in dynamical systems with fractional derivative elements. The proposed methodology offers a systematic treatment of uncertainties in spectrum-based stochastic simulation and their propagation for response determination of systems with memory-dependent or viscoelastic behavior. A key advantage of the framework lies in its ability to model the variability of estimated PSD functions using a non-parametric probabilistic representation, while explicitly accounting for frequency-domain correlations that are typically overlooked in conventional PSD-based estimates. First, a “relaxed” version of the power spectral density is derived by extracting statistical moments across ensembles of discretized PSD estimates. Next, frequency-dependent truncated normal distributions are employed to capture PSD uncertainties. Statistically compatible realizations are generated using three distinct sampling strategies: a single-variable inverse cumulative distribution function-based method for efficient sampling of marginal probability density functions, a multivariate Gaussian approach that incorporates cross-frequency covariance to capture global correlation structure, and an Ornstein–Uhlenbeck Markov process model, which reconstructs smoothly correlated PSD trajectories. The efficiency of the proposed approach is demonstrated by considering three representative case studies. These are a Duffing nonlinear oscillator with fractional damping, a tuned mass-damper-inerter system with nonlinear coupling characteristics, and a nonlinear vibration energy harvester under stochastic excitation. It is shown that by accounting for a comprehensive probabilistic treatment of the PSD, the proposed framework yields enhanced reliability analysis results of dynamical systems under spectral uncertainty.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111647"},"PeriodicalIF":11.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267746","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}
Yun Ye , Pengjun Zheng , Pengpeng Xu , Qiaoqiao Ren , Ran Yan , Xiaowei Gao
{"title":"Varying effects of risk factors on economic losses from fishing vessel accidents: A Bayesian random-parameter quantile regression with heterogeneity in means","authors":"Yun Ye , Pengjun Zheng , Pengpeng Xu , Qiaoqiao Ren , Ran Yan , Xiaowei Gao","doi":"10.1016/j.ress.2025.111690","DOIUrl":"10.1016/j.ress.2025.111690","url":null,"abstract":"<div><div>Understanding the determinants of economic loss in fishing vessel accidents is crucial for maritime risk assessment and policy development. This study proposes a Bayesian Random-Parameter Quantile Regression with Heterogeneity in Means (BRPQRHM) framework, and compares it with the Bayesian fixed-parameter regression (BFPR), Bayesian fixed-parameter quantile regression (BFPQR), and Bayesian random-parameter quantile regression (BRPQR) to investigate the varying and heterogeneous effects of vessel, environment, and accident-related factors on economic loss. The proposed approach addresses key limitations of conventional models by offering three major advantages by enabling a richer characterization of covariate effects across quantiles, improving robustness to outliers in heavy-tailed and skewed data, and accounting for unobserved heterogeneity through random parameters influenced by covariates. Using a dataset of fishing vessel accidents in Ningbo waters, the results demonstrate substantial variations in covariate effects across quantiles and highlight the superiority of quantile regression in modeling the skewed and heavy-tailed distribution of economic losses. The BRPQR and BRPQRHM models significantly improve model fit at higher quantiles and reveal that the effects of variables such as human errors and crew qualifications are probabilistic rather than fixed. In particular, the BRPQRHM model at the 98% quantile captures complex interactions between crew effects and contextual factors, including vessel width, visibility, and accident type. These findings underscore the importance of accounting for the unobserved heterogeneity and provide novel insights into the risk factors associated with severe fishing vessel accidents.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111690"},"PeriodicalIF":11.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049743","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}
Chengpeng Wan , Long Shao , Liang Fan , Desheng Cao , Jinfen Zhang
{"title":"Spatiotemporal evolution of global maritime accidents: Integrating hot spot detection and severity modeling for system safety","authors":"Chengpeng Wan , Long Shao , Liang Fan , Desheng Cao , Jinfen Zhang","doi":"10.1016/j.ress.2025.111687","DOIUrl":"10.1016/j.ress.2025.111687","url":null,"abstract":"<div><div>As an important pillar of international trade, the shipping industry has become increasingly important in the global economy. However, the frequent occurrence of maritime transportation accidents has posed a threat to the human life safety and marine environment as well. In this study, we propose a novel integrated framework that combines spatiotemporal hotspot detection and severity-oriented risk modeling that combines spatial density analysis and emerging spatio-temporal hot spot analysis to investigate the evolutionary trend of global maritime accidents from both temporal and spatial dimensions, identifying accident hot spot waters, and analyzing the relationship between influencing factors (e.g., type of accident, type of vessel, and condition of ships) and the severity of accidents by using logistic regression models. The results indicate that the spatial distribution of maritime accidents has apparent hot spot agglomeration characteristics of dynamic evolutionary trends. The accident hot spot areas show significant changes in different time periods, which are mainly concentrated in the shipping-intensive areas. Similar trends are also seen in other shipping hub regions such as northwestern Europe, eastern North America and northwestern Africa. The study provides an important theoretical basis and practical guidance for the development of shipping safety management and accident prevention measures, which can help reduce the occurrence of maritime accidents and their severity.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111687"},"PeriodicalIF":11.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220549","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":"Intersection importance assessment for an operationally resilient urban traffic network: A multi-criteria decision-making-based framework","authors":"Mohammad Reza Valipour Malakshah, Zahra Amini","doi":"10.1016/j.ress.2025.111661","DOIUrl":"10.1016/j.ress.2025.111661","url":null,"abstract":"<div><div>Assessing the importance of intersections and identifying critical ones whose failure significantly impairs the operational efficiency of the urban traffic network is essential for effective transportation planning. Prior studies often rely on simplified network representations, single-method evaluations, or approaches limited by data availability. To overcome these shortcomings, there is a need for advanced network modeling and holistic evaluation of intersection importance, utilizing adaptable methods capable of functioning in the absence of complex data or expert-dependent input. This study proposes a practical and comprehensive framework to assess intersection importance, primarily leveraging objective Multi-Criteria Decision-Making (MCDM) methods. Particularly, the introduced approach models urban road networks as directed and weighted graphs using accessible foundational traffic characteristics data and their integrations derived through MCDM weighting methods. Intersection importance is then evaluated employing centrality measures and two-stage hybrid methods that combine these measures using MCDM weighting and ranking techniques. The weighting methods utilized include equal, entropy, CRITIC, CILOS, IDOCRIW, angular, Gini coefficient, and variance; the ranking methods applied include TOPSIS, VIKOR, SPOTIS, ARAS, COCOSO, CODAS, EDAS, MABAC, MAIRCA, MARCOS, and ELECTRE III. The performance of constructed objective methods is further compared with that of subjective approaches based on AHP and BWM. A case study of the urban road network of Philadelphia, United States, demonstrates the framework’s effectiveness. Results indicate that intersections with the highest strength and PageRank centrality scores in the constant-weight graph are identified as critical under mild and severe disruptions, respectively. Notably, MCDM-based hybrid methods outperform most centrality measures in assessing intersection importance, with objective hybrid methods performing comparably to subjective ones. Furthermore, spatial analysis reveals that first-tier critical intersections are located around the downtown periphery, highlighting it as a priority area for resilience-focused interventions.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111661"},"PeriodicalIF":11.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096667","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}
Huifang Niu , Jianchao Zeng , Hui Shi , Xiaohong Zhang , Wenjie Wang , Jianyu Liang , Guannan Shi
{"title":"Degradation modeling and remaining useful life prediction with dual-time-scale considering system state and individual variability","authors":"Huifang Niu , Jianchao Zeng , Hui Shi , Xiaohong Zhang , Wenjie Wang , Jianyu Liang , Guannan Shi","doi":"10.1016/j.ress.2025.111666","DOIUrl":"10.1016/j.ress.2025.111666","url":null,"abstract":"<div><div>Most recent studies on system degradation modeling and remaining useful life (RUL) prediction assume a stable system state, overlooking its influence on system degradation evolution. Additionally, individual variability among identical systems can affect the accuracy of the RUL prediction. To address these limitations, this study proposes a nonlinear Wiener process model with time-varying degradation rates that accounts for both system state and individual variability. The influence of fast-varying system states is captured using an average function, whereas individual variability is represented by a random-effect parameter. For cases where the system state changes rapidly while the degradation state evolves more slowly, a dual-time-scale Kalman filter algorithm is adopted to jointly estimate system state and random-effect parameters. The expectation–maximization algorithm is used to estimate the remaining unknown parameters of the degradation model. Furthermore, based on first hitting time definition, the approximate analytical expression for probability density function (PDF) of the RUL is derived. Finally, the effectiveness and practicality of proposed method are validated through both a numerical example and a motor case study.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111666"},"PeriodicalIF":11.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049614","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":"Langevin importance sampling for reliability analysis","authors":"Armin Tabandeh , Gaofeng Jia , Paolo Gardoni","doi":"10.1016/j.ress.2025.111634","DOIUrl":"10.1016/j.ress.2025.111634","url":null,"abstract":"<div><div>Importance Sampling (IS) is a widely used method for reliability analysis, designed to increase the frequency of samples from the failure domain by introducing a biased sampling density, known as the IS density. Recent Markov Chain simulation methods, such as Hamiltonian Monte Carlo (HMC), use artificial dynamics to improve sampling efficiency over conventional random-walk algorithms like Metropolis-Hastings. However, HMC can be inefficient in high-dimensional problems or when model evaluations are costly. This paper develops a novel approach, named Langevin IS, which reframes the inference problem in HMC as an optimization task for constructing the IS density. Central to this approach is the Langevin equation, which unifies various HMC variants within a general stochastic dynamics formulation. The proposed approach leverages Langevin dynamics to design a parametric IS density that approximately satisfies the associated Fokker–Planck equation. From this equation, a new distance measure is derived that incorporates geometric information absent in conventional criteria like the Kullback–Leibler divergence. An efficient algorithm is developed to solve the resulting optimization problem, incorporating surrogate modeling and active learning to reduce computational cost. A theoretical guarantee is also provided, showing that the estimation error is bounded in terms of the surrogate approximation error. The effectiveness of Langevin IS is demonstrated through benchmark reliability problems, highlighting its ability to deliver accurate failure probability estimates with improved efficiency.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111634"},"PeriodicalIF":11.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096707","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 seismic composite resilience model incorporating the recovery properties of serviceability and leakage for water distribution systems","authors":"Rongheng Zhao , Qiang Wu , Shi-Xiang Gu , Wenqi Du","doi":"10.1016/j.ress.2025.111664","DOIUrl":"10.1016/j.ress.2025.111664","url":null,"abstract":"<div><div>Post-earthquake restoration simulation process is an important step in conducting the seismic resilience analysis of water distribution systems (WDSs). Most of the existing simulation models neglect the isolation timing of pipelines with different damage degrees, tending to yield inaccurate seismic resilience assessment results. In addition, a single resilience index related to water supply capacity is usually considered in the existing studies, yet such individual indices may not fully represent the resilience characteristics of a WDS. To address these concerns, this study introduces a new restoration simulation model for WDSs based on key restoration events, which are defined as events changing the operation status (i.e., performance curve) of WDSs. Moreover, a seismic composite resilience model is proposed, by employing not only a water-supply-capacity parameter but also a leakage-related parameter as the resilience indices. Both proposed models are utilized to evaluate the seismic resilience and provide optimized restoration strategy for a WDS subjected to a moment magnitude 6.5 earthquake scenario. Comparative results demonstrate that the proposed models can result in desirable estimates of the performance curves of WDSs during restoration, and the leakage flow can be greatly reduced when the composite-resilience based restoration strategy is utilized. The models proposed could hopefully be utilized in engineering applications, such as guiding post-earthquake restorations of WDSs.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111664"},"PeriodicalIF":11.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049741","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":"Development of accident analysis for civil engineering structures an AcciMap diagram for collapsed steel dome structure","authors":"Hilmi Coskun, Sezer Sancar","doi":"10.1016/j.ress.2025.111686","DOIUrl":"10.1016/j.ress.2025.111686","url":null,"abstract":"<div><div>Accidents in the construction sector are often the subject of studies on work safety. These studies mostly focus on fatalities and injuries. However, accidents cause problems concerning construction processes as well. Accidents leading to structural collapses are an important subject that should be examined in this respect. These collapses can result from numerous causal factors. Therefore, a comprehensive accident analysis outlining the causes of steel structure collapses during construction is needed. This paper has 2 p.m. and the first is to determine the relationships among the causes of steel structure collapses using the six fundamental levels of AcciMap. The other purpose and the subject that makes the study novel is to show together causal factors that exist both during and before construction. In this context, the accident causality factors of a steel dome structure that collapsed during construction were determined by expert consultations. Based on expert evaluations, a Pareto analysis was conducted to identify the factors that contributed most significantly to the collapse. Among the 33 causal factors identified for the collapse, 15 were found to have existed pre-construction. Thus, one of the findings is that the chain of errors during construction is due to some systemic factors before construction. This study contributes to the literature by providing a framework for preventing accidents during the construction phase of steel structures.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111686"},"PeriodicalIF":11.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049611","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":"Risk assessment of strait-crossing routes using typhoon-induced multi-hazard environmental contours sampled from optimized hierarchical Archimedean copula models","authors":"Haoyu Li, Kai Wei","doi":"10.1016/j.ress.2025.111668","DOIUrl":"10.1016/j.ress.2025.111668","url":null,"abstract":"<div><div>Due to the rapid nature of economic development, the demand for strait-crossing passages is increasing, thereby highlighting the importance of rational route planning. However, the development of high-resolution marine environmental hazard maps is crucial for addressing the challenges faced by offshore structures and for conducting reliable route risk assessments. Therefore, a multi-hazard map is constructed for corridor risk assessment of a sea area acquisition system on the basis of sampling-based environmental contours. The Qiongzhou Strait is selected as the study area, and a marine environmental database of typhoons that have significantly impacted the study region is established on the basis of the constructed hybrid wind field and the SWAN + ADCIRC model. Then, optimal wind–wave–current–surge joint probability models are established via the HAC model combined with environmental databases. The multi-hazard map of 100-year load combinations in the strait passage is obtained through the direct sampling-based environmental contour method based on the optimized joint probability models. Finally, both subjective and objective methods are employed to conduct a route risk assessment. The results show that the constructed system can effectively satisfy the requirements. Furthermore, this study provides valuable references and technical support for coastal engineering design and multi-hazard corridor planning.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111668"},"PeriodicalIF":11.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049740","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}
Nicolás Ahumada , Juan Pablo Muñoz Gálvez , Alan Poulos , Félix Rojas , Juan Carlos de la Llera
{"title":"Seismic fragility estimation of electrical substations accounting for component damage and short circuit faults","authors":"Nicolás Ahumada , Juan Pablo Muñoz Gálvez , Alan Poulos , Félix Rojas , Juan Carlos de la Llera","doi":"10.1016/j.ress.2025.111671","DOIUrl":"10.1016/j.ress.2025.111671","url":null,"abstract":"<div><div>Modern society relies heavily on electricity, which is transmitted from generating stations to final consumers through an electrical power grid. Electrical substations are key components of these grids. Previous earthquakes have heavily damaged some of these substations, affecting their functionality and leading to service interruptions. Functionality losses are usually modeled using fragility functions, which in general terms relate a seismic intensity measure with the probability of failure. Most previous studies use generic substation fragility functions that are not specific to the modeled substations. Indeed, power substations are composed of several internal components laid out in a wide range of different configurations, which cannot be accurately represented by these generic models. This study proposes a method to construct fragility functions based on the internal configuration of substation components and accounts for faults to individual lines within the substation and short circuit faults that render all the substation nonfunctional. The proposed method was applied to Chilean substations, resulting in fragility functions that vary significantly depending on their voltage level and their internal configuration. On average, the resulting fragility functions are fairly similar to the generic functions provided by HAZUS. However, fragility functions of individual substation archetypes can differ significantly between each other and with those of HAZUS. Thus, using fragility functions that consider a more realistic internal configuration of electrical components instead of generic functions can improve estimations of seismic performance, risk, and resilience of electric power grids, and hence help in providing better tools to prepare and mitigate earthquake effects.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111671"},"PeriodicalIF":11.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096835","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}