Resilient Cities and Structures最新文献

{"title":"Editorial: From performance-based engineering to cityscape resilience","authors":"Alice Alipour , Gian Paolo Cimellaro , Xinzheng Lu","doi":"10.1016/j.rcns.2024.08.001","DOIUrl":"10.1016/j.rcns.2024.08.001","url":null,"abstract":"","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages A1-A2"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000395/pdfft?md5=eff6ede1fee6c6d0c14d7a273686caff&pid=1-s2.0-S2772741624000395-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142098959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-disciplinary seismic resilience modeling for developing mitigation policies and recovery planning","authors":"Milad Roohi ,&nbsp;Saeid Ghasemi ,&nbsp;Omar Sediek ,&nbsp;Hwayoung Jeon ,&nbsp;John W. van de Lindt ,&nbsp;Martin Shields ,&nbsp;Sara Hamideh ,&nbsp;Harvey Cutler","doi":"10.1016/j.rcns.2024.07.003","DOIUrl":"10.1016/j.rcns.2024.07.003","url":null,"abstract":"<div><p>The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling. These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes. This paper presents a multi-disciplinary seismic resilience modeling methodology to assess the vulnerability of the built environment and economic systems. This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of communities. Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective. The <em>engineering model</em> is developed using a probabilistic fragility-based modeling approach and is analyzed using Monte Carlo (MC) simulations subject to seismic multi-hazard, including simulated ground shaking and resulting liquefaction of the soil, to quantify the physical damage to buildings and electric power substations (EPS). The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency. The <em>economic model</em> consists of a spatial computable general equilibrium (SCGE) model that aggregates commercial buildings into sectors for retail, manufacturing, services, etc., and aggregates residential buildings into a wide range of household groups. The SCGE model employs building functionality estimates to quantify the economic losses. The outcomes of this integrated modeling consist of engineering and economic impact metrics, which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals. An illustrative case study of Salt Lake County (SLC), Utah, developed through an extensive collaborative partnership and engagement with SLC officials, is presented. The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems, the impacts on capital stock, employment, and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 66-84"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000309/pdfft?md5=5423f887d8555c5cc2342ad610d67cd6&pid=1-s2.0-S2772741624000309-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141736685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Community-Level resilience analysis using earthquake-tsunami fragility surfaces","authors":"Mojtaba Harati,&nbsp;John W. van de Lindt","doi":"10.1016/j.rcns.2024.07.006","DOIUrl":"10.1016/j.rcns.2024.07.006","url":null,"abstract":"<div><p>This study introduces an advanced community-level resilience analysis methodology integrating 3D fragility surfaces for combined successive earthquake-tsunami hazard and analysis. The methodology facilitates comprehensive evaluations of spatial damage, economic loss, and risk under multi-hazard conditions. This study compares earthquake-only analysis results to the successive earthquake-tsunami analysis at the community level to reveal – and quantify - significant disparities in damage and loss estimations between the analyses, emphasizing the need to consider both hazards in community planning even at lower seismic intensities. Critical assessment of the FEMA combinational rule demonstrates its limitations in accurately predicting losses and damage patterns at higher hazard intensities, highlighting the necessity for refined models that accurately account for hazard interactions. This research advances multi-hazard community-level resilience analysis by offering a robust framework for earthquake and tsunami assessment, underscoring the need for integration of detailed multi-hazard analyses into resilience planning. Finally, it suggests future directions for enhancing framework applicability across diverse community settings and structural types, aiming to improve community resilience.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 101-115"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000334/pdfft?md5=c5c8f82051b494f00d6ddd67f71b3cf6&pid=1-s2.0-S2772741624000334-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilience of coastal bridges under extreme wave-induced loads","authors":"Jesika Rahman,&nbsp;Vahid Aghaeidoost,&nbsp;AHM Muntasir Billah","doi":"10.1016/j.rcns.2024.07.002","DOIUrl":"10.1016/j.rcns.2024.07.002","url":null,"abstract":"<div><p>Records of wave-induced damage on coastal bridges during natural hazards have been well documented over the past two decades. It is of utmost importance to decipher the loading mechanism and enhance the resilience of coastal bridges during extreme wave-inducing events. Quantification of vulnerability of these structures is an essential step in designing a resilient bridge system. Recently, considerable efforts have been made to study the force applied and the response of coastal bridge systems during extreme wave loading conditions. Although remarkable progress can be found in the quantification of load and response of coastal superstructures, very few studies assessed coastal bridge resiliency against extreme wave-induced loads. This paper adopts a simplified and practical technique to analyze and assess the resilience of coastal bridges exposed to extreme waves. Component-level and system-level fragility analyses form the basis of the resiliency analysis where the recovery functions are adopted based on the damage levels. It is shown that wave period has the highest contribution to the variation of bridge resiliency. Moreover, this study presents the uncertainty quantification in resiliency variation due to changes in wave load intensity. Results show that the bridge resiliency becomes more uncertain as the intensity of wave parameters increases. Finally, possible restoration strategies based on the desired resilience level and the attitude of decision-makers are also discussed.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 85-100"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000292/pdfft?md5=1256cf731cf632a79d7b8c5c9a9a2540&pid=1-s2.0-S2772741624000292-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141949923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Upcrossing‐based time‐dependent resilience of aging structures","authors":"Cao Wang","doi":"10.1016/j.rcns.2024.05.001","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.05.001","url":null,"abstract":"<div><p>The time-dependent resilience of an in-service aging structure provides quantitative measure of the structural ability to prepare for, adapt to, withstand and recover from disruptive events. Resilience models have been proposed in the literature to evaluate the resilience of aging structures subjected to discrete load processes, which are, however, not applicable to handle resilience problems considering continuous load processes. In this paper, a new method is developed to evaluate the time-dependent resilience of aging structures subjected to a continuous load process. The proposed method serves as the complement of the existing resilience models addressing discrete load processes, and takes into account the aging effects of the structural resistance/capacity and the nonstationarity in loads as a result of climate change. A structure suffers from a damage state upon the occurrence of an upcrossing of the load effect with respect to the resistance/capacity, leading to the reduction of the performance function, followed by a recovery process that restores the performance. The proposed method enables the time-dependent resilience to be evaluated via a closed form solution. It is also revealed that, the proposed resilience model takes an extended form of the existing formula for upcrossing-based time-dependent reliability, thus establishing a unified framework for the two quantities. The applicability of the proposed method is demonstrated through examining the time-dependent resilience of a residential building subjected to wind load. The effects of key factors on resilience, including the nonstationarity and correlation structure of the load process, as well as the resistance/capacity deterioration scenario, are investigated through an example. In particular, the structural resilience would be overestimated if ignoring the potential impacts of climate change, which is a relatively non-conservative evaluation.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 3","pages":"Pages 20-27"},"PeriodicalIF":0.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000206/pdfft?md5=81cc27d896415ae0fe3d85c5a4276d28&pid=1-s2.0-S2772741624000206-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141240298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protecting critical infrastructure against cascading effects: The PRECINCT approach","authors":"Meisam Gordan ,&nbsp;Djibrilla Amadou Kountche ,&nbsp;Daniel McCrum ,&nbsp;Stefan Schauer ,&nbsp;Sandra König ,&nbsp;Shirley Delannoy ,&nbsp;Lorcan Connolly ,&nbsp;Mircea Iacob ,&nbsp;Nicola Gregorio Durante ,&nbsp;Yash Shekhawat ,&nbsp;Carlos Carrasco ,&nbsp;Takis Katsoulakos ,&nbsp;Páraic Carroll","doi":"10.1016/j.rcns.2024.04.001","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.04.001","url":null,"abstract":"<div><p>Critical Infrastructures (CIs), which serve as the foundation of our modern society, are facing increasing risks from cyber threats, physical attacks, and natural disasters. Additionally, the interdependencies between CIs throughout their operational lifespan can also significantly impact their integrity and safety. As a result, enhancing the resilience of CIs has emerged as a top priority for many countries, including the European Union. This involves not only understanding the threats/attacks themselves but also gaining knowledge about the areas and infrastructures that could potentially be affected. A European Union-funded project named PRECINCT (Preparedness and Resilience Enforcement for Critical INfrastructure Cascading Cyber-Physical Threats), under the Horizon 2020 program, tries to connect private and public stakeholders of CIs in a specific geographical area. The key objective of this project is to establish a common cyber-physical security management approach that will ensure the protection of both citizens and infrastructures, creating a secure territory. This paper presents the components of PRECINCT, including a directory of PRECINCT Critical Infrastructure Protection (CIP) blueprints. These blueprints support CI communities in designing integrated ecosystems, operating and replicating PRECINCT components (or toolkits). The integration enables coordinated security and resilience management, incorporating improved 'installation-specific' security solutions. Additionally, Serious Games (SG), and Digital Twins (DT) are a significant part of this project, serving as a novel vulnerability evaluation method for analysing complicated multi-system cascading effects in the PRECINCT Living Labs (LLs). The use of SG supports the concentrated advancement of innovative resilience enhancement services.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 3","pages":"Pages 1-19"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277274162400019X/pdfft?md5=aa07d28098cb25ad38e744b952c0d8ba&pid=1-s2.0-S277274162400019X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140951904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-optimization based target reliabilities for design of structures exposed to fire","authors":"Ranjit Kumar Chaudhary ,&nbsp;Thomas Gernay ,&nbsp;Ruben Van Coile","doi":"10.1016/j.rcns.2024.03.004","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.03.004","url":null,"abstract":"<div><p>Adequacy of structural fire design in uncommon structures is conceptually ensured through cost-benefit analysis where the future costs are balanced against the benefits of safety investment. Cost-benefit analyses, however, are complicated and computationally challenging, and hence impractical for application to individual projects. To address this issue, design guidance proposes target reliability indices for normal design conditions, but no target reliability indices are defined for structural fire design. We revisit the background of the cost-optimization based approach underlying normal design target reliability indices then we extend this approach for the case of fire design of structures. We also propose a modified objective function for cost-optimization which simplifies the evaluation of target reliability indices and reduces the number of assumptions. The optimum safety level is expressed as a function of a new dimensionless variable named “Damage-to-investment indicator” (<em>DII</em>). The cost optimization approach is validated for the target reliability indices for normal design condition. The method is then applied for evaluating <em>DII</em> and the associated optimum reliability indices for fire-exposed structures. Two case studies are presented: (i) a one-way loaded reinforced concrete slab and (ii) a steel column under axial loading. This study thus provides a framework for deriving optimum (target) reliability index for structural fire design which can support the development of rational provisions in codes and standards.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 20-33"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000073/pdfft?md5=8c93ba8b1c17594c2da41aa96012b1d9&pid=1-s2.0-S2772741624000073-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140339775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of effects of hazard geometry and mitigation strategies on community resilience under tornado hazards using an Agent-based modeling approach","authors":"Xu Han ,&nbsp;Maria Koliou","doi":"10.1016/j.rcns.2024.03.003","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.03.003","url":null,"abstract":"<div><p>A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions. The effect of the hazard geometry (center and angle of tornado path as well as the tornado width) is studied herein on how it influences the recovery of physical and social systems within the community. Given that pre-disaster preparedness including mitigation strategies (e.g., retrofits) and policies (e.g., insurance) is crucial for increasing the resilience of the community and facilitating a faster recovery process, in this study, the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties. The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling (ABM) approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies. The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems (lifeline networks, schools, healthcare, businesses, and households). The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 1-19"},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000061/pdfft?md5=388d219140ec9b89a5f251b325989c5b&pid=1-s2.0-S2772741624000061-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating extreme event attribution into climate change adaptation for civil infrastructure: Methods, benefits, and research needs","authors":"Yating Zhang ,&nbsp;Bilal M. Ayyub ,&nbsp;Juan F. Fung ,&nbsp;Zachary M. Labe","doi":"10.1016/j.rcns.2024.03.002","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.03.002","url":null,"abstract":"<div><p>In the last decade, the detection and attribution science that links climate change to extreme weather and climate events has emerged as a growing field of research with an increasing body of literature. This paper overviews the methods for extreme event attribution (EEA) and discusses the new insights that EEA provides for infrastructure adaptation. We found that EEA can inform stakeholders about current climate risk, support vulnerability-based and hazard-based adaptations, assist in the development of cost-effective adaptation strategies, and enhance justice and equity in the allocation of adaptation resources. As engineering practice shifts from a retrospective approach to a proactive, forward-looking risk management strategy, EEA can be used together with climate projections to enhance the comprehensiveness of decision making, including planning and preparing for unprecedented extreme events. Additionally, attribution assessment can be more useful for adaptation planning when the exposure and vulnerability of communities to past events are analyzed, and future changes in the probability of extreme events are evaluated. Given large uncertainties inherent in event attribution and climate projections, future research should examine the sensitivity of engineering design to climate model uncertainties, and adapt engineering practice, including building codes, to uncertain future conditions. While this study focuses on adaptation planning, EEA can also be a useful tool for informing and enhancing decisions related to climate mitigation.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 1","pages":"Pages 103-113"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277274162400005X/pdfft?md5=610b5f5962d80f07407d5404ba40234c&pid=1-s2.0-S277274162400005X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140162740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning prediction models for ground motion parameters and seismic damage assessment of buildings at a regional scale","authors":"Sanjeev Bhatta ,&nbsp;Xiandong Kang ,&nbsp;Ji Dang","doi":"10.1016/j.rcns.2024.03.001","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.03.001","url":null,"abstract":"<div><p>This study examines the feasibility of using a machine learning approach for rapid damage assessment of reinforced concrete (RC) buildings after the earthquake. Since the real-world damaged datasets are lacking, have limited access, or are imbalanced, a simulation dataset is prepared by conducting a nonlinear time history analysis. Different machine learning (ML) models are trained considering the structural parameters and ground motion characteristics to predict the RC building damage into five categories: null, slight, moderate, heavy, and collapse. The random forest classifier (RFC) has achieved a higher prediction accuracy on testing and real-world damaged datasets. The structural parameters can be extracted using different means such as Google Earth, Open Street Map, unmanned aerial vehicles, etc. However, recording the ground motion at a closer distance requires the installation of a dense array of sensors which requires a higher cost. For places with no earthquake recording station/device, it is difficult to have ground motion characteristics. For that different ML-based regressor models are developed utilizing past-earthquake information to predict ground motion parameters such as peak ground acceleration and peak ground velocity. The random forest regressor (RFR) achieved better results than other regression models on testing and validation datasets. Furthermore, compared with the results of similar research works, a better result is obtained using RFC and RFR on validation datasets. In the end, these models are utilized to predict the damage categories of RC buildings at Saitama University and Okubo Danchi, Saitama, Japan after an earthquake. This damage information is crucial for government agencies or decision-makers to respond systematically in post-disaster situations.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 1","pages":"Pages 84-102"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000048/pdfft?md5=d8fbc4dce242235d9a3f487633f83d32&pid=1-s2.0-S2772741624000048-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140163206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}