Resilient Cities and Structures最新文献

{"title":"Modelling infrastructure interdependencies and cascading effects using temporal networks","authors":"Gian Paolo Cimellaro ,&nbsp;Alessandro Cardoni ,&nbsp;Andrei Reinhorn","doi":"10.1016/j.rcns.2024.05.002","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.05.002","url":null,"abstract":"<div><p>Lifelines are critical infrastructure systems characterized by a high level of interdependency that can lead to cascading failures after any disaster. Many approaches can be used to analyze infrastructural interdependencies, but they are usually not able to describe the sequence of events during emergencies. Therefore, interdependencies need to be modeled also taking into account the time effects. The methodology proposed in this paper is based on a modified version of the Input-output Inoperability Model and returns the probabilities of failure for each node of the system. Lifelines are modeled using graph theory, while perturbations, representing a natural or man-made disaster, are applied to the elements of the network following predetermined rules. The cascading effects among interdependent networks have been simulated using a spatial multilayer approach, while the use of an adjacency tensor allows to consider the temporal dimension and its effects. The method has been tested on a case study based on the 2011 Fukushima Dai-ichi nuclear disaster. Different configurations of the system have been analyzed and their probability of occurrence evaluated. Two models of the nuclear power plant have been developed to evaluate how different spatial scales and levels of detail affect the results.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 3","pages":"Pages 28-42"},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000218/pdfft?md5=7eeb0606098ed6928dbc02d58fd351bb&pid=1-s2.0-S2772741624000218-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141240295","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":"Spatial correlation in building seismic performance for regional resilience assessment","authors":"Tian You ,&nbsp;Solomon Tesfamariam","doi":"10.1016/j.rcns.2024.06.004","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.06.004","url":null,"abstract":"<div><p>Probabilistic seismic performance assessment method for buildings offers a valuable approach to simulate the broader regional impacts: economic losses, downtime, and casualties. A crucial aspect of this process entails accounting for the spatial correlation of building performances, aiming for an accurate estimation of the probability of extreme regional losses, such as the simultaneous collapse of buildings with similar structural characteristics. In this study, a correlation model based on a Gaussian random field is employed, and several key challenges associated with its application are addressed. In addition, efficiency of five different methods of selecting station records from the same earthquake scenario is compared. The minimum number of earthquake records necessary to achieve a stable correlation result is determined. Additionally, spatial correlations derived from different history earthquake events are compared. By addressing these critical issues, this research contributes to refining the reliability of probabilistic methods for regional resilience assessment.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 57-65"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000267/pdfft?md5=c62ae50771ecfc3ed038d00908ecace0&pid=1-s2.0-S2772741624000267-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141478880","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":"Digital twin approach for enhancing urban resilience: A cycle between virtual space and the real world","authors":"Yixing Wang ,&nbsp;Qingrui Yue ,&nbsp;Xinzheng Lu ,&nbsp;Donglian Gu ,&nbsp;Zhen Xu ,&nbsp;Yuan Tian ,&nbsp;Shen Zhang","doi":"10.1016/j.rcns.2024.06.002","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.06.002","url":null,"abstract":"<div><p>Construction of disaster-resilient cities has attracted considerable attention. However, traditional methods of studying urban disaster resilience through experimental approaches are often constrained by various limitations, such as testing sites, costs and ethical considerations. To address these constraints, this paper proposes incorporating digital twin concepts into urban disaster resilience research. By establishing a connection between the physical realm of the city and its virtual counterpart, this approach utilizes digital simulations to overcome the limitations of experimental methods and enables dynamic deduction and control of the disaster process. This paper delves into three key aspects encompassing the acquisition of data from reality to the virtual space, disaster simulation within the virtual space, and translation of virtual insights into effective disaster prevention strategies in reality. It provides a comprehensive summary of relevant research endeavors from the authors’ research group and showcases the effectiveness and potential of the proposed techniques. These findings serve as references for pre-disaster planning, real-time emergency assessments, post-disaster rescue operations, and accident investigations for buildings and cities.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 34-45"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000231/pdfft?md5=acb5c8dda347acc12345c08ef6843bfe&pid=1-s2.0-S2772741624000231-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141303353","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":"Bayesian network-based resilience assessment of interdependent infrastructure systems under optimal resource allocation strategies","authors":"Jingran Sun ,&nbsp;Kyle Bathgate ,&nbsp;Zhanmin Zhang","doi":"10.1016/j.rcns.2024.06.001","DOIUrl":"https://doi.org/10.1016/j.rcns.2024.06.001","url":null,"abstract":"<div><p>Critical infrastructure systems (CISs) play a key role in the socio-economic activity of a society, but are exposed to an array of disruptive events that can greatly impact their function and performance. Therefore, understanding the underlying behaviors of CISs and their response to perturbations is needed to better prepare for, and mitigate the impact of, future disruptions. Resilience is one characteristic of CISs that influences the extent and severity of the impact induced by extreme events. Resilience is often dissected into four dimensions: robustness, redundancy, resourcefulness, and rapidity, known as the “4Rs”. This study proposes a framework to assess the resilience of an infrastructure network in terms of these four dimensions under optimal resource allocation strategies and incorporates interdependencies between different CISs, with resilience considered as a stochastic variable. The proposed framework combines an agent-based infrastructure interdependency model, advanced optimization algorithms, Bayesian network techniques, and Monte Carlo simulation to assess the resilience of an infrastructure network. The applicability and flexibility of the proposed framework is demonstrated with a case study using a network of CISs in Austin, Texas, where the resilience of the network is assessed and a “what-if” analysis is performed.</p></div>","PeriodicalId":101077,"journal":{"name":"Resilient Cities and Structures","volume":"3 2","pages":"Pages 46-56"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772741624000243/pdfft?md5=24619a7f8da93c2785ae149da66b3b9e&pid=1-s2.0-S2772741624000243-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141444203","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":"Editorial: From performance-based engineering to cityscape resilience","authors":"Alice Alipour ,&nbsp;Gian Paolo Cimellaro ,&nbsp;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}