Structural SafetyPub Date : 2024-01-24DOI: 10.1016/j.strusafe.2024.102442
Taro Yaoyama, Tatsuya Itoi, Jun Iyama
{"title":"Probabilistic model updating of steel frame structures using strain and acceleration measurements: A multitask learning framework","authors":"Taro Yaoyama, Tatsuya Itoi, Jun Iyama","doi":"10.1016/j.strusafe.2024.102442","DOIUrl":"10.1016/j.strusafe.2024.102442","url":null,"abstract":"<div><p><span>This paper proposes a multitask learning framework for probabilistic model updating by jointly using strain and acceleration measurements. This framework can enhance the structural damage assessment and response prediction of existing steel frame structures with quantified uncertainty. Multitask learning may be used to address multiple similar inference tasks simultaneously to achieve a more robust prediction performance by transferring useful knowledge from one task to another, even in situations of data scarcity. In the proposed model-updating procedure, a spatial frame is decomposed into multiple planar frames that are viewed as multiple tasks and jointly analyzed based on the hierarchical Bayesian model, leading to robust estimation results. The procedure uses a displacement–stress relationship in the modal space because it directly reflects the elemental stiffness and requires no prior knowledge concerning the mass, unlike most existing model-updating techniques. Validation of the proposed framework by using a full-scale vibration test on a one-story, one-bay by one-bay moment resisting steel frame, wherein structural damage to the column bases is simulated by loosening the </span>anchor bolts, is presented. The experimental results suggest that the displacement–stress relationship has sufficient sensitivity toward localized damage, and the Bayesian multitask learning approach may result in the efficient use of measurements such that the uncertainty involved in model parameter estimation is reduced. The proposed framework facilitates more robust and informative model updating.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102442"},"PeriodicalIF":5.8,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139555970","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}
Structural SafetyPub Date : 2024-01-23DOI: 10.1016/j.strusafe.2024.102444
U. Bhardwaj, A.P. Teixeira, C. Guedes Soares
{"title":"Calibration of burst strength models of corroded pipelines using the hierarchical Bayesian method","authors":"U. Bhardwaj, A.P. Teixeira, C. Guedes Soares","doi":"10.1016/j.strusafe.2024.102444","DOIUrl":"10.1016/j.strusafe.2024.102444","url":null,"abstract":"<div><p>This paper proposes a probabilistic framework to calibrate burst strength models of intact and corroded pipelines based on the hierarchical Bayesian method. The approach uses burst test data of intact and corroded pipelines of different steel grades compiled from the literature and accounts for the variations among the data sources. First, the most appropriate burst strength models for corrosion-free and corroded pipelines are adopted. The burst pressure prediction models are categorised under low, medium and high-grade steel classes. Using the hierarchical Bayesian approach model uncertainty factors are derived to calibrate the burst strength models. The mean values and uncertainty of posterior probabilities of the model uncertainty factors are estimated for intact and corroded pipelines in three material categories. This study further investigates the uncertainty propagated by calibrated and non-calibrated models and draws important observations regarding the uncertainty associated with the calibration. The prediction uncertainties follow a non-linear increasing trend as corrosion defect increases. This study's importance is demonstrated with a case study that shows the differences in the uncertainty resulting from the use of the proposed approach compared to the conventional method. Additionally, for corroded pipes, model uncertainty factors are described as a function of defect depth with regression parameters estimated from hierarchical Bayesian-based regression analysis. Finally, a comparison between calibrated and non-calibrated models indicates that the calibrated models provide non-conservative predictions.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102444"},"PeriodicalIF":5.8,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167473024000158/pdfft?md5=7a729f4829186e0b2872c3c8428bb482&pid=1-s2.0-S0167473024000158-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139587275","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}
Structural SafetyPub Date : 2024-01-20DOI: 10.1016/j.strusafe.2024.102445
Cristóbal H. Acevedo , Marcos A. Valdebenito , Iván V. González , Héctor A. Jensen , Matthias G.R. Faes , Yong Liu
{"title":"Control variates with splitting for aggregating results of Monte Carlo simulation and perturbation analysis","authors":"Cristóbal H. Acevedo , Marcos A. Valdebenito , Iván V. González , Héctor A. Jensen , Matthias G.R. Faes , Yong Liu","doi":"10.1016/j.strusafe.2024.102445","DOIUrl":"10.1016/j.strusafe.2024.102445","url":null,"abstract":"<div><p>Estimation of second-order statistics allows characterizing the uncertainty associated with the response of stochastic finite element models. Two common approaches for estimating these statistics are Monte Carlo simulation and perturbation. The purpose of this paper is to present a framework to aggregate the results obtained by means of these two approaches under the umbrella of Control Variates with Splitting. This allows to produce estimates of the second-order statistics of the system’s response with improved precision and accuracy. More specifically, Control Variates is implemented in such a way that the variance of the estimates of second-order statistics is minimized. In addition, the application of intervening variables for enhancing perturbation is considered as well, showing substantial advantages by increasing the accuracy of the estimates of second-order statistics. The application of the proposed framework is illustrated by means of an example involving the estimation of second-order statistics of a model involving confined seepage flow.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102445"},"PeriodicalIF":5.8,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016747302400016X/pdfft?md5=5b2e5d5de55b963ac4b0934b14678c8b&pid=1-s2.0-S016747302400016X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139515544","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}
Structural SafetyPub Date : 2024-01-19DOI: 10.1016/j.strusafe.2024.102443
Jingran He , Junjie Hong , Ruofan Gao , Jinju Tao , Hongmin Yan
{"title":"Stochastic modelling of in-structure concrete strength based on stochastic damage model and Burr distribution","authors":"Jingran He , Junjie Hong , Ruofan Gao , Jinju Tao , Hongmin Yan","doi":"10.1016/j.strusafe.2024.102443","DOIUrl":"10.1016/j.strusafe.2024.102443","url":null,"abstract":"<div><p>The probability measure of low-quality concrete is essential for the reliability analysis of concrete structures. However, this problem is usually neglected, and the normal distribution or lognormal distribution is often selected as the probability distribution of concrete strength. In this study, a better solution for this problem is given by theoretically deriving of the Burr distribution based on the stochastic damage model. A large amount of in-situ test data in engineering structures is applied to perform a K-S test of different distribution types and to fit the distribution parameters. As a result, the advantage of Burr distribution in representing the tail probability is explained by both theoretical derivation and fitting results. And the Burr distribution is accepted by the K-S test in every strength grade while the other distribution types are all partly rejected.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102443"},"PeriodicalIF":5.8,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139498006","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}
Structural SafetyPub Date : 2024-01-19DOI: 10.1016/j.strusafe.2024.102440
C. Sheng , Q.Y. Fan , H.P. Hong
{"title":"Estimating intraevent and interevent variability and spatial correlation of tropical cyclone wind fields and their use for the risk assessment of a portfolio of structures","authors":"C. Sheng , Q.Y. Fan , H.P. Hong","doi":"10.1016/j.strusafe.2024.102440","DOIUrl":"10.1016/j.strusafe.2024.102440","url":null,"abstract":"<div><p>Often the tropical cyclone (TC) wind hazard assessment requires the use of the TC wind field model. While theoretical models typically predict the observed wind field well, there can be a spatially varying residual correlation that impacts the damage assessment of communities or groups of structures. In this study, we focus on developing spatial correlation models and assessing the intraevent and interevent variability of the TC wind field using the H*Wind dataset and two widely used wind field models - the vertically averaged boundary layer slab model and the gradient wind field-based model. Our models and the statistics of the interevent and intraevent variability are integrated into a framework for evaluating the wind-induced damage of a portfolio of structures. The framework includes simulating TC tracks and wind fields, considering interevent and intraevent variabilities, and assessing peak linear elastic and nonlinear responses. Numerical examples illustrating the use of this framework are provided, indicating that realistic spatial correlation of the TC wind field needs to be considered to assess the correlation coefficient of the damage factor of a pair of spatially distributed structures and the probability distribution of the damage cost of a portfolio of structures.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102440"},"PeriodicalIF":5.8,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139515545","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}
Structural SafetyPub Date : 2024-01-18DOI: 10.1016/j.strusafe.2024.102439
Shuangmin Shi , Nelson Lam , Yiwen Cui , Guoxing Lu , Emad Gad , Lihai Zhang
{"title":"Life-cycle performance of aluminium cladding panels in resisting hailstorms","authors":"Shuangmin Shi , Nelson Lam , Yiwen Cui , Guoxing Lu , Emad Gad , Lihai Zhang","doi":"10.1016/j.strusafe.2024.102439","DOIUrl":"10.1016/j.strusafe.2024.102439","url":null,"abstract":"<div><p>This paper delves into cumulative damage on aluminium cladding panels attributed to hailstorms throughout the lifespan of the installations. 40 gas gun tests subjecting the cladding panel to repeated impact were undertaken for the purpose of studying cumulative damage behaviour. Insights from these tests were integrated into a hail size distribution model to characterise the probabilistic distribution of permanent indentation resulted from multiple hailstorm events. A life-cycle analysis framework was subsequently introduced, incorporating the natural variability of hailstone sizes and dynamic response of claddings to repeated ice impact. Intervention criterion can be established based on knowledge of the accumulation of permanent indentation into the cladding panels. Proactive actions are recommended should the indentations become visible to prevent worsening damage. Randomness of hailstorm occurrences was considered using hazard function which can be inferred from historical observations. Practical application of the proposed model is illustrated through case studies of two Australian states, coupled with comparative analyses highlighting key factors influencing cladding performance. The ability to account for stochasticity distinguishes the presented framework from existing deterministic approaches.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102439"},"PeriodicalIF":5.8,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167473024000109/pdfft?md5=081f65d63c65acb90a2d20878b58b889&pid=1-s2.0-S0167473024000109-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139497960","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}
Structural SafetyPub Date : 2024-01-18DOI: 10.1016/j.strusafe.2024.102441
Yihan Shao, Yazhou Xie
{"title":"Seismic risk assessment of highway bridges in western Canada under crustal, subcrustal, and subduction earthquakes","authors":"Yihan Shao, Yazhou Xie","doi":"10.1016/j.strusafe.2024.102441","DOIUrl":"10.1016/j.strusafe.2024.102441","url":null,"abstract":"<div><p>This study conducts seismic risk assessment of highway bridges in western Canada. The performance-based earthquake engineering (PBEE) framework is enhanced to assess the expected annual repair cost ratio (ARCR) and annual restoration time (ART) of a benchmark bridge class under the region’s three types of earthquakes - shallow crustal earthquakes (CEs), deep subcrustal earthquakes (SCEs), and megathrust Cascadia subduction earthquakes (CSEs). First, event-specific seismic hazard models are considered, whereas event-consistent ground motions are selected for non-linear time history analyses. Compared with those from CEs and SCEs, CSE ground motions feature a much longer duration. This long-duration effect is captured by validating the numerical model of the bridge column against (1) a cyclic pushover test under standard versus long-duration loading protocols and (2) a shaking table test excited by six consecutive ground motions. Besides, the Park and Ang damage index is utilized as the column’s engineering demand parameter (EDP) and updated as a demand-capacity ratio model when reaching four different damage states. A comprehensive list of ground motion intensity measures (IMs) is considered where the spectra acceleration at one second, <em>S<sub>a</sub></em>(1.0), is chosen as the most suitable IM based on its performance in proficiency, efficiency, practicality, and EDP-IM correlation across all three earthquake events. Subsequently, component- and system-level fragility models are derived under each earthquake type using the <em>cloud</em> analysis that convolves the seismic demands with capacity models for multiple bridge components. To further quantify and propagate the epistemic uncertainty associated with the development of probabilistic seismic demand models (PSDMs), the bootstrap resampling technique is utilized to generate numerous seismic demand datasets and develop a stochastic set of seismic fragility curves. Finally, the bootstrapped, event-dependent fragility models are combined with the respective hazard models and probabilistic loss functions to assess the expected ARCR and ART for the benchmark bridge class. This study underscores the significantly higher seismic risk of highway bridges when facing CSEs, followed by CEs and SCEs.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102441"},"PeriodicalIF":5.8,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167473024000122/pdfft?md5=3f866428852cd30cf9bfa39c28df1f99&pid=1-s2.0-S0167473024000122-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139497913","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}
Structural SafetyPub Date : 2024-01-09DOI: 10.1016/j.strusafe.2024.102430
Dade Lai , Fabrizio Nocera , Cristoforo Demartino , Yan Xiao , Paolo Gardoni
{"title":"Probabilistic models of dynamic increase factor (DIF) for reinforced concrete structures: A Bayesian approach","authors":"Dade Lai , Fabrizio Nocera , Cristoforo Demartino , Yan Xiao , Paolo Gardoni","doi":"10.1016/j.strusafe.2024.102430","DOIUrl":"https://doi.org/10.1016/j.strusafe.2024.102430","url":null,"abstract":"<div><p><span>The response of structures under rapidly varying loads can be affected by strain rate sensitivity generally expressed using Dynamic Increase Factor (</span><span><math><mrow><mi>D</mi><mi>I</mi><mi>F</mi></mrow></math></span>). Current models for estimating the <span><math><mrow><mi>D</mi><mi>I</mi><mi>F</mi></mrow></math></span> in Reinforced Concrete (RC) structures are generally deterministic and have restricted applicability due to their dependence on limited experimental data resulting in bias. This paper overcomes these limitations by proposing three probabilistic models that quantify compressive and tensile concrete and steel <span><math><mrow><mi>D</mi><mi>I</mi><mi>F</mi></mrow></math></span><span><span>, accounting for the relevant uncertainties. The proposed models are based on existing deterministic models with the addition of probabilistic correction terms. Bayesian updating<span> is employed to estimate the unknown model parameters using observational data from a large collection of experimental observations. The models incorporate model uncertainties stemming from assumed model form and (potential) missing variables through a model error term. The proposed probabilistic models are used to evaluate the reliability of RC structures under dynamic loads. As an illustration, the proposed probabilistic models are used to estimate the reliability of an example RC column under combined dynamic axial force and moment, and a RC column or beam under dynamic bending moments resulting in cracking. In the two examples, we consider the ACI 318-19 requirements for Ultimate Limit State (ULS) and </span></span>Serviceability Limit States (SLS). In comparison to deterministic </span><span><math><mrow><mi>D</mi><mi>I</mi><mi>F</mi></mrow></math></span> models, the proposed probabilistic models yield enhanced predictive accuracy, presenting a practical and robust approach to assess the structural reliability under impact and blast loads.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102430"},"PeriodicalIF":5.8,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139434503","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}
Structural SafetyPub Date : 2023-12-23DOI: 10.1016/j.strusafe.2023.102429
Zi-Tong Zhao , He-Qing Mu , Ka-Veng Yuen
{"title":"Probability density function modelling and credible region construction for multivariate, asymmetric, and multimodal distributions of geotechnical data","authors":"Zi-Tong Zhao , He-Qing Mu , Ka-Veng Yuen","doi":"10.1016/j.strusafe.2023.102429","DOIUrl":"10.1016/j.strusafe.2023.102429","url":null,"abstract":"<div><p>Geotechnical data are typically Multivariate, Uncertain, and Irregular (MUI), so the probability distribution of geotechnical data is Multivariate, Asymmetric, and Multimodal (MAM). Probability Density Function (PDF) modelling and Credible Region (CR) construction are two key issues for a MAM distribution. There are two fundamental difficulties in characterizing a MAM distribution. The first is on joint PDF modelling as many traditional approaches collapse for a MAM distribution. Copula theory has attracted special attention for this purpose but very few works attempted to tackle the critical problem of probabilistic prediction on target variables using available information of remaining variables based on the copula-based joint PDF. The second is on CR construction of a MAM distribution as it cannot find a unique CR of a MAM distribution given an exceedance probability only. There is still a lack of a unified approach for CR construction for a MAM distribution of geotechnical data. Aiming to resolve these two fundamental difficulties, we propose the BAyeSIan Copula-based Highest density region/contour (BASIC-H) for providing a systematic framework of PDF modelling and CR construction of a MAM distribution. This framework contains Stage-PDF and Stage-CR. Stage-PDF fuses the copula theory and Bayesian inference to develop optimal, robust, and hyper-robust predictions on the posterior distribution and posterior predictive distribution. Stage-CR adopts the constraint for the CR that the probability density of every point inside the CR is at least as large as the probability density of any point outside, which is the same as the idea of the HDR (Highest Density Region). The Monte Carlo Simulation (MCS), based on the developed optimal, robust, and hyper-robust posterior distributions and posterior predictive distributions, is performed for estimation of the probability density boundary, which is a key parameter for constructing the HDR. Examples using simulated data and Quaternary clay data are presented to illustrate the capabilities of the BASIC-H in PDF modelling and CR construction of MAM distributions of geotechnical data.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"107 ","pages":"Article 102429"},"PeriodicalIF":5.8,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139031806","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}
Structural SafetyPub Date : 2023-12-10DOI: 10.1016/j.strusafe.2023.102428
Salim Idris Malami , Dimitri V. Val , Benny Suryanto , Husham A. Salman , Xiao-Hui Wang
{"title":"Probabilistic approach to the sustainability assessment of reinforced concrete structures in conditions of climate change","authors":"Salim Idris Malami , Dimitri V. Val , Benny Suryanto , Husham A. Salman , Xiao-Hui Wang","doi":"10.1016/j.strusafe.2023.102428","DOIUrl":"10.1016/j.strusafe.2023.102428","url":null,"abstract":"<div><p>The paper presents a probabilistic method based on two methodologies – Life Cycle Cost Analysis (LCCA) and Life Cycle Assessment (LCA), for evaluating the sustainability of reinforced concrete (RC) structures in terms of their costs and CO<sub>2</sub> emissions. The method considers the whole life of a RC structure by taking into account CO<sub>2</sub> initially embodied in its construction materials, the absorption of CO<sub>2</sub> by concrete due to carbonation during the service life of the structure, potential damage to the structure due to carbonation-induced corrosion of reinforcing steel that may require repairs, and relevant costs. Since there are numerous uncertainties associated with the calculation of CO<sub>2</sub> emissions and costs, a probabilistic approach is beneficial. The emphasis is made on RC structures made of the so-called “green concretes”, in which Portland cement is partially replaced with supplementary cementitious materials such as fly ash and ground granulated blast-furnace slag. The issue of a changing climate is also addressed. The method is illustrated by assessing the sustainability of a multi-story RC carpark made of different concrete types at three different locations (London, Paris and Marseille) for present and future climate conditions. This assessment's results show that using green concretes leads to a major reduction in CO<sub>2</sub> emissions and a small decrease in the life-cycle cost of the carpark RC elements. The relative sustainability performance of green concretes slightly improves compared to Portland cement concrete for future climate conditions.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"107 ","pages":"Article 102428"},"PeriodicalIF":5.8,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167473023001157/pdfft?md5=90884fbdac61741f95a119ffcedc3a16&pid=1-s2.0-S0167473023001157-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138569559","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}