Structural Safety最新文献

{"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":"2025-04-27","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":"Efficient reliability analysis for offshore wind turbines: Leveraging SVM and augmented oversampling technique","authors":"Xukai Zhang,&nbsp;Arash Noshadravan","doi":"10.1016/j.strusafe.2025.102597","DOIUrl":"10.1016/j.strusafe.2025.102597","url":null,"abstract":"<div><div>This study develops an efficient reliability assessment method designed to optimize maintenance strategies for Offshore Wind Turbines (OWT), aiming for significant cost savings through reduced maintenance frequency and enhanced efficiency. Effective cost management requires a robust and accurate approach for reliability-based lifecycle management. Therefore, this paper introduces an improved predictive maintenance method, grounded on the reliability-based failure probability of OWT systems. To augment computational efficiency and diminish computational time, a surrogate model is proposed for the estimation of failure probability. This surrogate model integrates the classification strengths of Support Vector Machine (SVM) with an augmented Synthetic Minority Oversampling Technique (SMOTE), specifically adapted for extremely imbalanced data. The study’s contributions are twofold: firstly, it develops a novel reliability-based predictive maintenance method allowing for the quantitative assessment of OWTs’ current conditions; secondly, it presents a surrogate model adept at managing extreme data imbalance, thereby enhancing prediction accuracy. The effectiveness of the surrogate model is validated through a case study under two distinct weather conditions. The proposed predictive maintenance method serves as an efficient and effective tool for improved maintenance planning for OWTs.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102597"},"PeriodicalIF":5.7,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877330","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":"The probabilistic inverse problem and its solving method based on probability density evolution theory and convex optimization algorithms","authors":"Yuhan Zhu,&nbsp;Jie Li","doi":"10.1016/j.strusafe.2025.102600","DOIUrl":"10.1016/j.strusafe.2025.102600","url":null,"abstract":"<div><div>A probabilistic inverse problem-solving method based on the framework of Probability Density Evolution Theory and convex optimization algorithms is proposed. This method reformulates the identification of the random source as a quadratic programming problem with linear constraints, identifying the probability density function of the random source in a physical stochastic system even when the distribution type of the random source is entirely unknown. Through singular value decomposition of the quadratic matrix, an error analysis is performed, revealing that the solvability of the probabilistic inverse problem fundamentally depends on the injectivity of the mapping from the random source space to the response space. Case studies confirm that the proposed method is not sensitive to prior information and does not require any predefined assumptions about the distribution type. Meanwhile, it can preliminarily determine whether the inverse problem is solvable before the computational process begins.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102600"},"PeriodicalIF":5.7,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877329","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":"2025-04-21","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":"Probabilistic life-cycle assessment of landslides exposed to both rainfall under nonstationary climate change effects and earthquakes","authors":"Zhengying He ,&nbsp;Mitsuyoshi Akiyama ,&nbsp;Abdul Kadir Alhamid ,&nbsp;Dan M. Frangopol ,&nbsp;Yu Huang","doi":"10.1016/j.strusafe.2025.102599","DOIUrl":"10.1016/j.strusafe.2025.102599","url":null,"abstract":"<div><div>Combined effects of rainfall and seismic hazards pose significant threats to structures and infrastructure systems. Additionally, climate change is projected to impact the intensity and frequency of future rainfall, increasing the likelihood of landslides. However, evaluating long-term landslide probability under the combined effects of rainfall and seismic hazards, while considering nonstationary climate change, presents significant challenges due to the distinct characteristics of their occurrence processes. This study introduces a novel framework for probabilistic life-cycle landslide assessment that systematically integrates climate change effects on rainfall hazard along with seismic hazard. Probabilistic nonstationary rainfall and seismic hazard models are developed by leveraging stochastic renewal process theory based on occurrence probability and the associated hazard intensity distribution. Slope fragility assessments are conducted for four event scenarios: individual rainfall, individual earthquake, rainfall followed by an earthquake, and an earthquake followed by rainfall, using seepage and equivalent linear analysis through Monte Carlo simulation. Finally, using the total probability theorem, life-cycle landslide probability is numerically evaluated by convolving nonstationary rainfall and seismic hazards with slope fragilities. An illustrative example is provided by applying the proposed framework to a slope in Hiroshima city, Japan, to explore how the combined effects between nonstationary rainfall and seismic hazards impact life-cycle landslide probability.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102599"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874554","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":"2025-03-27","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}

{"title":"A phase-control-based method for the simulation of homogeneous random fields of fluctuating wind speed","authors":"Jia-Hang Lyu ,&nbsp;Jian-Bing Chen ,&nbsp;Pol D. Spanos ,&nbsp;Jie Li","doi":"10.1016/j.strusafe.2025.102593","DOIUrl":"10.1016/j.strusafe.2025.102593","url":null,"abstract":"<div><div>The simulation of stochastic processes, and of time-variant random fields finds extensive applications across various scientific and engineering domains. Despite the existence of a variety of methods, including the well-developed spectral representation method, it is still necessary to study the representation of the correlation structure of time-variant random fields. This paper proposes a phase control method for simulating correlated stochastic processes and spatiotemporal random fields. First, by introducing an auxiliary random phase angle and controlling its amplitude, the correlation of two stochastic processes can be precisely reproduced by introducing the auxiliary phase angle to the original process. Further, for time-variant random field simulation, the correlation structure of the random field is converted into that of the random phase angle field, thereby making it possible for the random field simulation either by phase shifting from a single process or using the spectral representation method in a decoupled manner. The effectiveness of the proposed method is validated by two numerical examples of fluctuating wind field simulation. This method provides an alternative perspective on the correlation structure of random fields and could be used for conditional simulation of random fields in future work.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102593"},"PeriodicalIF":5.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682072","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":"Reliability-based quantification of the benefits of machine learning predictive models in seismic structural design and performance assessment","authors":"Muneera A. Aladsani,&nbsp;Henry V. Burton","doi":"10.1016/j.strusafe.2025.102596","DOIUrl":"10.1016/j.strusafe.2025.102596","url":null,"abstract":"<div><div>Machine Learning (ML) techniques have been used extensively in research within the field of structural engineering due to their high level of accuracy in predicting the behavior of different structural elements. In fact, the superior predictive performance relative to traditional statistical models is often suggested as the primary motivation for the adoption of ML models. However, the implications of such improvements in predictive accuracy in the design and performance of structural systems have not been studied. This paper presents a reliability-based investigation of the tangible benefits provided by ML models in terms of structural design and performance. To quantify these benefits, the increase in predictive accuracy is interpreted as a reduction in epistemic uncertainty. The specific focus is on a predictive model that estimates the drift capacity of reinforced concrete shear walls (RCSWs) with special boundary elements. The accuracy of an extreme gradient boosting (XGBoost) model relative to a basic linear regression equation is quantified in terms of reduced epistemic uncertainty. Then, using 36 RCSW archetype buildings, a Monte Carlo-based procedure is implemented to evaluate the implication of the improved predictive accuracy to seismic design and performance. The study provides insights into how much improvement in accuracy (i.e., ML relative to traditional model) is needed to have a tangible effect on the seismic design and performance.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102596"},"PeriodicalIF":5.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705452","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":"2025-03-18","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":"Physical-informed random field technique for virtual modelling based building probabilistic vulnerability assessment","authors":"Zhiyi Shi ,&nbsp;Yuan Feng ,&nbsp;Mark G. Stewart ,&nbsp;Wei Gao","doi":"10.1016/j.strusafe.2025.102595","DOIUrl":"10.1016/j.strusafe.2025.102595","url":null,"abstract":"<div><div>Developing a probabilistic vulnerability assessment framework for bushfire-prone buildings is a critical measure to reduce bushfire-induced risks to life safety and economic losses to an acceptable level. A reliable assessment approach should include multiple probability-based macro indicators by considering their inherent uncertainties. These macro indicators can incorporate the efficiency of bushfire-damaged transportation network at specified moments, the geographical position of buildings, among others. A Physics-Informed Random Field-Virtual Modelling (PIRF-VM) framework for probabilistic vulnerability assessment of bushfire-prone buildings in large-scale bushfire incidents is proposed. The PIRF generates a random field-based, multi-physical information-fusion model for the simulation of bushfire spread in a large-scale approximate natural environment. The integrated physical information includes the spatially varying vegetation characteristics, the Digital Elevation Model (DEM)-based terrain, the terrain-shaped time-dependent wind field, the geographical coordinates of roads and buildings. To mitigate the computational burden posed by stochastic bushfire simulations in PIRF, the VM is introduced. It can establish an explicit functional relationship between input physical information and output responses of interest, such as the remaining time for bushfire reaching a specified location. As a result, for any new input physical information, the output responses can be directly predicted without time-consuming simulations. Benefiting from the efficient predictions of the PIRF-VM, several probability-based macro indicators are simultaneously considered when assessing the probabilistic vulnerability for bushfire-prone buildings in large-scale bushfire incidents. The Australian community of Cowan serves as an example to illustrate the practical application of the proposed scheme, demonstrating potential in constructing more bushfire-resilient communities in the face of bushfire hazards.</div></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"115 ","pages":"Article 102595"},"PeriodicalIF":5.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682070","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}