Structural Safety最新文献

{"title":"Modeling probabilistic micro-scale wind field for risk forecasts of power transmission systems during tropical cyclones","authors":"Xiubing Huang,&nbsp;Naiyu Wang","doi":"10.1016/j.strusafe.2025.102620","DOIUrl":"10.1016/j.strusafe.2025.102620","url":null,"abstract":"<div><div>Tropical cyclones (TCs) pose significant risks to power transmission systems, causing extensive damage, widespread outages and severe socio-economic impacts. While reliable risk forecasting of these systems during TCs hinges on accurate wind predictions, operational numerical weather prediction (NWP) models struggle to deliver unbiased, high-resolution probabilistic wind-field forecasts necessary for infrastructure risk projections. This study introduces the Probabilistic Micro-Scale Wind-Field model (ProbMicro-WF) designed to enhance real-time hazard modeling for power system risk forecasts during TC evolution. This model improves NWP wind forecast by achieving the following: 1) probabilistic calibration and bias correction for NWP wind forecasts, leveraging historical TC observational data to improve prediction accuracy at high wind speeds; 2) terrain-modified statistical downscaling that translates mesoscale forecasts to micro-scale wind fields, capturing localized wind dynamics critical for tower- and transmission line-specific risk evaluation; and 3) a spatiotemporal stochastic model that preserves wind-field correlation structures, mitigating systemic underestimation of risk variance across geographically dispersed infrastructure during TC evolution. Finally, the ProbMicro-WF model is applied to the power transmission system in Zhejiang Province, China (105,500 km²) during Super Typhoon Lekima in 2019, highlighting its capability to simulate spatially coherent, high-resolution wind fields, enabling robust pre-event mitigation and real-time grid management in TC-prone regions.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102620"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195770","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":"Impact of structural information fidelity on reduced-order model development for regional risk assessment","authors":"Sang-ri Yi ,&nbsp;Alexandros A. Taflanidis ,&nbsp;Parisa Toofani Movaghar ,&nbsp;Carmine Galasso","doi":"10.1016/j.strusafe.2025.102602","DOIUrl":"10.1016/j.strusafe.2025.102602","url":null,"abstract":"<div><div>Reduced-order models (ROMs) are widely used for seismic vulnerability estimation, both for approximating the response of specific structures as well as for modeling a portfolio of buildings within regional risk assessment applications. There are different ROM modeling approaches with different degrees of complexity, and the modeling choice, as well as the accuracy of the estimated response, naturally depends on the fidelity of the available information for developing the ROM. For regional risk assessment applications, the ROM implementation is commonly established using an automated workflow that leverages generic information about basic building characteristics to derive the mechanical parameters of the simulation models. This paper investigates the influence of information fidelity on the downstream risk analysis when utilizing ROMs in such a context, focusing specifically on moment-resisting frames (MRFs). Initially, a framework for establishing multi-degree-of-freedom (MDoF) ROMs with hysteretic nonlinear behavior is presented, establishing rulesets to derive nominal values of ROM parameters from commonly available building descriptions such as number of stories, story height, design specifications, or structural system type and its material(s) (e.g., reinforced concrete or steel). The rulesets place emphasis on explicitly modeling differences across stories instead of relying on simplified approximations that utilize equivalence to inelastic single-degree-of-freedom systems. The fidelity of the information for developing the ROM is quantified by assigning probability distributions over the aforementioned nominal values, with different degrees of uncertainty across the different parameters. Parametric and global sensitivity analyses are then performed to investigate the importance of this information fidelity. A computational workflow leveraging resampling principles is discussed to promote computational efficiency in these analyses. The results provide unique insights into the parameters of critical importance for establishing ROMs for different MDoF archetypes and offer guidance for the type of data that needs to be collected with higher fidelity (degree of confidence) when deploying ROMs in regional scale seismic risk assessment, in order to improve the prediction accuracy.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102602"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084524","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":"Improved variance estimation for subset simulation by accounting for the correlation between Markov chains","authors":"Qingqing Miao,&nbsp;Ying Min Low","doi":"10.1016/j.strusafe.2025.102606","DOIUrl":"10.1016/j.strusafe.2025.102606","url":null,"abstract":"<div><div>Subset simulation (SS) is a popular structural reliability analysis method, especially for problems characterized by low failure probabilities and high-dimensional complexities. Unlike most variance reduction methods, SS obviates the need for prior domain information, making it versatile across diverse applications. Markov chain Monte Carlo (MCMC) algorithms are required for sampling from an unknown conditional distribution, resulting in correlated samples. There is plenty of literature on SS in several aspects, such as the improvement of MCMC algorithms, and combining SS with other techniques. However, one aspect that appears to be neglected concerns the variance estimation crucial for assessing the accuracy of the probability estimate. To date, most studies on SS still rely on the conventional variance estimation method, which only considers the correlation within a Markov chain (intrachain) but neglects the correlation across separate chains (interchain) and different subset levels (interlevel). This study aims to improve understanding of this topic and develop a more accurate variance estimation method for SS. An investigation based on multiple independent SS runs reveal that the intrachain, interchain and interlevel correlations are all important. Subsequently, a new variance estimation method is proposed to account for the intrachain and interchain correlations. The proposed method is easy to apply, has small sampling uncertainty and only utilizes samples from a single SS run. Results indicate a notable improvement in accuracy compared to the conventional method.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102606"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928318","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":"Structural reliability analysis using gradient-enhanced physics-informed neural network and probability density evolution method","authors":"Zidong Xu,&nbsp;Hao Wang,&nbsp;Kaiyong Zhao,&nbsp;Han Zhang","doi":"10.1016/j.strusafe.2025.102604","DOIUrl":"10.1016/j.strusafe.2025.102604","url":null,"abstract":"<div><div>In past decade, probability density evolution method (PDEM) has become one of the most popular approaches to conduct overall structural reliability analysis (SRA). The main procedure of the PDEM-based SRA lies in solving the generalized probability density evolution equation (GDEE) related to virtual stochastic process (VSP). Common methods for GDEE solving are highly sensitive to the choice of solving parameters, which may affect the accuracy, efficiency and stability of the solution. Recently, physics-informed neural network (PINN) and its extended form have successfully utilized to solve differential equations in different fields. With this in view, the gradient-enhanced PINN (gPINN) are utilized to solve the GDEE of the VSP for SRA, which leads to an improved approach, termed as evolutionary probability density (EPD)-gPINN model. Specifically, the normalized GDEE and the additional gradient residual equations are derived as the physical loss. Meanwhile, to offer sufficient supervised training data, an easy-to-operate data augmentation procedure is established. Numerical examples are posed for validating the validity of the proposed framework. Parametric analysis is conducted to investigate the influence of the network parameters to the predictive performance. Results indicate that using proper weight of the gradient loss, the proposed framework can efficiently conduct the SRA, whose predictive performance outperforms PINN.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102604"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902246","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":"Modeling the spatial corrosion of strand and FE-based Monte Carlo simulation for structural performance assessment of deteriorated PC beams","authors":"Taotao Wu ,&nbsp;Mitsuyoshi Akiyama ,&nbsp;De-Cheng Feng ,&nbsp;Sopokhem Lim ,&nbsp;Dan M. Frangopol ,&nbsp;Zhejun Xu","doi":"10.1016/j.strusafe.2025.102605","DOIUrl":"10.1016/j.strusafe.2025.102605","url":null,"abstract":"<div><div>Structural performance assessments of corroded prestressed concrete (PC) beams using numerical models that account for spatial corrosion distribution and are validated against experimental results remain limited compared to those of reinforced concrete (RC) beams. This study proposes a probabilistic analysis method to evaluate the structural performance of corroded PC beams, incorporating the spatial corrosion distribution of strands and wires. The method is further applied to compare the structural performance of corroded PC and RC beams. Three finite element (FE) models are developed and compared for their accuracy in predicting the structural behavior of PC beams: (a) using the mean steel weight loss of the strand, (b) incorporating the spatial corrosion distribution of the strand, and (c) considering the spatial corrosion distribution of the six outer wires. The model incorporating the spatial corrosion distribution of the six outer wires achieves the highest accuracy, as it effectively simulates the first wire breakage that governs the flexural load-bearing and deflection ductility capacities of PC beams. The probabilistic distribution parameters representing the spatial variability of corrosion are derived from experimental data. Using this distribution, Monte Carlo simulation-based spatial corrosion samples are integrated into the most accurate FE model to obtain the probability density functions (PDFs) of corroded PC beams. The results indicate that PC beams with the same total steel weight loss can exhibit significantly different flexural load-bearing and deflection ductility capacities due to spatial variability, underscoring the importance of a probabilistic assessment. Furthermore, the PDFs of PC members are shifted to the left compared to those of RC members with the same degree of corrosion. Notably, early wire breakage results in lower mean values and standard deviations for the deflection ductility of corroded PC beams compared to RC beams.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102605"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924023","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":"Optimizing uncertainty estimation in Enhanced Monte Carlo methods","authors":"Konstantinos N. Anyfantis","doi":"10.1016/j.strusafe.2025.102617","DOIUrl":"10.1016/j.strusafe.2025.102617","url":null,"abstract":"<div><div>The probability of failure serves as a key metric in a structural reliability analysis, but its accurate estimation remains computationally demanding, particularly for low-probability failure events. The Enhanced Monte Carlo (EMC) method has been developed in order to alleviate from inefficiencies due to the high number of required simulations. Recent advancements integrate Machine Learning techniques with the EMC to further accelerate the estimation process. However, a critical limitation of EMC lies in its fitted confidence interval (CI) estimation, which tends to overestimate uncertainty, leading to unnecessary computational overhead. This study proposes a new prescriptive CI formulation constructed from the method’s hyperparameters, offering a more accurate and computationally efficient approach to uncertainty quantification. The method is general and can be applied to any reliability problem that can be described by a probability curve. The effectiveness of the proposed method is demonstrated through a benchmark reliability problem and a real-world marine structural application. The results indicate significant improvements in efficiency without compromising accuracy, paving the way for enhanced structural reliability assessments.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102617"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134106","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":"Corrigendum to “Evaluating the importance of spatial variability of corrosion initiation parameters for the risk-based maintenance of reinforced concrete marine structures” [Struct. Saf. 114 (2025) 102568]","authors":"Romain Clerc ,&nbsp;Charbel-Pierre El-Soueidy ,&nbsp;Franck Schoefs","doi":"10.1016/j.strusafe.2025.102618","DOIUrl":"10.1016/j.strusafe.2025.102618","url":null,"abstract":"","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"116 ","pages":"Article 102618"},"PeriodicalIF":5.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242447","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":"Frequency domain method for random vibration analysis of nonlinear systems under time-varying coherent nonstationary excitations","authors":"Ning Zhao ,&nbsp;Xu Wang ,&nbsp;Yu Wu ,&nbsp;Fengbo Wu ,&nbsp;Shaomin Jia","doi":"10.1016/j.strusafe.2025.102601","DOIUrl":"10.1016/j.strusafe.2025.102601","url":null,"abstract":"<div><div>Strong earthquakes, downbursts, and typhoons are extreme events that involve time-varying coherent excitations, which are crucial in accurately analyzing the structural response. However, most current methods for nonstationary random vibration analysis assume time-invariant coherence, which fails to capture the time-varying nature of real-world excitations. To address this gap, this study proposes an effective and efficient frequency domain analysis framework for nonlinear systems under time-varying coherent nonstationary excitations. This framework is grounded in the equivalent linearization technique and an enhanced evolutionary spectral method (EESM). Through the use of the equivalent linearization technique, a series of equivalent linear systems replaces the initial nonlinear system; with EESM, the highly efficient analysis of time-varying coherent nonstationary random vibrations in linear systems can be performed, requiring only a limited number of time history analyses and fast Fourier transform operations. For local nonlinear systems, the efficient frequency domain method is more favorable in terms of efficiency due to the explicit calculation advantages of EESM. The specific applications for Duffing system and hysteretic system are presented to demonstrate the reliable accuracy and exceptional efficiency of this method, thereby showcasing its potential in addressing large-scale nonlinear system problems.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102601"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891928","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 refined TMCMC algorithm for adaptive model updating for the probabilistic analysis of complex engineering structures","authors":"Yu-Xiao Wu ,&nbsp;De-Cheng Feng ,&nbsp;Shi-Zhi Chen","doi":"10.1016/j.strusafe.2025.102582","DOIUrl":"10.1016/j.strusafe.2025.102582","url":null,"abstract":"<div><div>Modelling complex engineering structures involves numerous parameters that are difficult to determine. Many uncertainties in the model parameters cannot be resolved through standards and experiments alone, necessitating model updating methods. The Bayesian model updating method is one of the most popular approaches for this purpose; and it has led to the development of numerous improved algorithms. However, the traditional Bayesian model updating algorithms are time-consuming and may not always yield the most likely posterior distributions of the model parameters in engineering applications. Therefore, this paper introduces a refined transitional Markov chain Monte Carlo (rTMCMC) algorithm based on the TMCMC algorithm and improved TMCMC (iTMCMC) algorithm. The rTMCMC algorithm is an adaptive Bayesian model updating method designed for engineering applications; it can adaptively find the most likely posterior distributions of model parameters without increasing the computation time. The efficiency of the rTMCMC algorithm is validated via a numerical example, which compares it with the TMCMC and iTMCMC algorithms. Finally, two examples at both the component and structural levels, updated by the rTMCMC algorithm, and compared with the iTMCMC algorithm, are presented, demonstrating the effectiveness of the rTMCMC algorithm in engineering applications.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102582"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682071","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":"Seismic risk and failure modes assessment of steel BRB frames under earthquake sequences","authors":"Fernando Gutiérrez-Urzúa ,&nbsp;Fabio Freddi ,&nbsp;Enrico Tubaldi","doi":"10.1016/j.strusafe.2025.102598","DOIUrl":"10.1016/j.strusafe.2025.102598","url":null,"abstract":"<div><div>Buckling-Restrained Braces (BRBs) are characterized by steady and nearly symmetric hysteretic loops, providing large energy dissipation capacity under strong earthquakes. These devices are designed to sustain a specified maximum ductility demand and, if not properly designed, may fail due to excessive inelastic deformations. Moreover, their low post-yielding stiffness may lead the structure to large residual inter-story drifts at the end of the earthquake motion, and the cumulative ductility demand due to repeated plastic excursions may lead to low-cycle fatigue failure of the device core. The risk of reaching either of these failure modes is exacerbated when considering multiple earthquakes. Although BRBs are designed to function as a fuse element, there is a lack of consensus on the criteria for replacement, particularly when large residual deformations are not observed. Recent studies have suggested that BRBs can withstand several loading cycles before developing low-cycle fatigue rupture; thus, the decision to replace a BRB after a single ground motion may be overly conservative. The present study investigates the likelihood of BRBs reaching these failure modes within a stochastic framework that considers the probability of occurrence of multiple earthquakes during the structure’s lifetime. For this purpose, two steel Moment Resisting Frames (MRFs) retrofitted with BRBs are numerically modeled in OpenSees and subjected to the cumulative demand from hazard-consistent multiple earthquake sequences. The demand values are compared with multiple capacity models for low-cycle fatigue in the BRB core, as well as conventional limits for residual drifts and other failure modes. The outcomes of this study suggest that the risk of developing low-cycle fatigue in BRBs is negligible, even when multiple ground motions are considered, while other failure modes are significantly more likely to occur, particularly when the structures are subjected to pulse-like ground motions.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102598"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769048","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}