Resilient Cities and Structures最新文献

Traditionally, nonlinear time history analysis (NLTHA) is used to assess the performance of structures under future hazards which is necessary to develop effective disaster risk management strategies. However, this method is computationally intensive and not suitable for analyzing a large number of structures on a city-wide scale. Surrogate models offer an efficient and reliable alternative and facilitate evaluating the performance of multiple structures under different hazard scenarios. However, creating a comprehensive database for surrogate modelling at the city level presents challenges. To overcome this, the present study proposes meta databases and a general framework for surrogate modelling of steel structures. The dataset includes 30,000 steel moment-resisting frame buildings, representing low-rise, mid-rise and high-rise buildings, with criteria for connections, beams, and columns. Pushover analysis is performed and structural parameters are extracted, and finally, incorporating two different machine learning algorithms, random forest and Shapley additive explanations, sensitivity and explainability analyses of the structural parameters are performed to identify the most significant factors in designing steel moment resisting frames. The framework and databases can be used as a validated source of surrogate modelling of steel frame structures in order for disaster risk management.

Earthquake is one of the natural disasters that affects the buildings and communities in developing countries. It causes different levels of damages to the buildings, making them uninhabitable for a period of time, called downtime (DT). This paper proposes a Fuzzy Logic hierarchical method to estimate the downtime of residential buildings in developing countries after an earthquake. The use of expert-based systems allows quantifying the indicators involved in the model using descriptive knowledge instead of hard data, accounting also for the uncertainties that may affect the analysis. The applicability of the methodology is illustrated using the information gathered after the 2015 Gorkha, Nepal, earthquake as a case study. On April 25, 2015, Nepal was hit by the Mw 7.8 Gorkha earthquake, which damaged and destroyed more than 500.000 residential buildings. Information obtained from a Rapid Visual Damage Assessment (RVDA) is used through a hierarchical scheme to evaluate the building damageability. Sensitivity analysis based on Sobol method is implemented to evaluate the importance of parameters gathered in the RVDA for building damage estimation. The findings of this work may be used to estimate the restoration time of damaged buildings in developing countries and to plan preventive safety measures.

The nonductile reinforced concrete building (NDRCB) stock—typically, pre-1974 structures in the U.S.—is a well-known high-risk group for seismic hazards. Prior studies indicate that there are approximately 1500 NDRCBs in Los Angeles. Through various ordinances, the owners are currently required to choose between demolition and, when appropriate, seismic retrofitting. Because fulfilling these ordinances will take decades, the potential risk of major losses will persist. In this study, a method for automated development of structural analysis models and damage fragilities for non-ductile moment-resisting frames is established. This capability enables seismic risk assessment at a regional scale using relatively limited building metadata and the era-specific seismic design code. The approach is used first to develop archetypal models in OpenSees, verified through static pushover and nonlinear time-history analyses against prior detailed studies. Fragility curves for discrete damage states are developed through a probabilistic seismic demand model. Additional investigations are carried out to consider the influence of soil-structural interaction effects and to determine the most suitable seismic intensity measures to quantify the seismic damage levels of NDRCB frames. The sensitivity of the proposed modeling method to variations/uncertainties in building configurations and properties is also examined through parametric studies. The method is limited to a particular subcategory of NDRBCs—namely, moment-resisting frames—but extensions to other types appear straightforward.

Resilient infrastructure is critical to a sustainable and functioning society. Infrastructure management and (re)development are highly complex processes encompassing various stakeholders’ interests while they are pressured by the uncertainty of climate change and social transition. In response to these challenges, various resilience initiatives emerged with different motivations and approaches. The purpose of this research is to understand the interplay between motivations and organizational approaches as well as resilience conceptualization. This can provide insights into which domains of resilience have been focused on and what needs to be improved in their organizational approaches to realize motivations. This research specifically investigates ten resilient infrastructure initiatives in the Netherlands. By using scoping review and content analysis, our results highlight that resilience initiatives conceptualize resilience in different ways, mainly focusing on built and organizational resilience with a focus on long-term and wider geographic scope. Each initiative had several motivations, including 1) creating innovative solutions, 2) sharing knowledge, 3) promoting commitment and cooperation, and 4) promoting resilience. These motivations are reflected in the organizational approach. For example, there was a strong link between the motivation ‘creating shared knowledge’ and the organizational approach ‘research collaboration.’ Generic motivation such as ‘promoting resilience’ does not have one mainstreaming approach, which shows promoting resilience in practice is still in the exploration stage. This research provides major motivations and organizational approaches and their link within the resilient infrastructure initiatives which can contribute to better organizing similar initiatives aiming for resilient infrastructure.

Resilience assessment of transportation infrastructure is a crucial aspect of ensuring the continued functionality of a city or region in the face of various disruptions. However, these infrastructures are also vulnerable to various types of disruptions, such as natural disasters. The ability of transportation infrastructures to withstand and recover from such disruptions is referred to as their resilience. This research presents a comprehensive framework to develop the resilience surface for assessing the resilience of transportation infrastructure such as bridges, roads, and tunnels. The framework involves the identification of the unique damage configurations through performing the fragility analysis, and the restoration of the infrastructures through developing recovery curves for each damage configuration by considering the relevant restoration data. The framework also considers the inherent uncertainty in the hazard intensity, modeling uncertainty, and restoration process. The framework is illustrated through the application to a case study of a highway bridge in Canada. The aim of this paper is to provide a useful tool for decision-makers to evaluate and improve the resilience of transportation infrastructures.

Fire is one of the extreme loading events that a building may experience during its service life and can have severe consequences on the safety of its occupants, first responders, and the structure. Steel framed buildings under severe fires can experience high levels of instability at a local or global level, which in turn can lead to the partial or progressive collapse of the structure. However, in current practice, fire resistance of structures is obtained without due consideration to a number of critical factors, and this is mainly due to the high level of complexity in undertaking advanced analysis of structures under fire exposure. This paper presents a parametric study on a ten-story braced steel framed building subjected to fire exposure wherein six different parameters are evaluated: fire severity, fire spread, load paths, temperature-induced creep, local instability, and analysis regime. Results from validated finite element models are utilized to evaluate the influence of the different parameters and recommend critical parameters to be incorporated in the analysis. Results show that the susceptibility of fire-induced progressive collapse significantly depends on the severity of the fire exposure scenario, including fire intensity, fire spread, and extent of burning. Also, accounting for the full effects of transient creep in fire-induced progressive collapse analysis is needed to obtain conservative failure times under severe to very intense fire exposure. Additionally, results from the parametric study infer that the sectional classification of a steel section based on local instability can alter under fire exposure and this effect is more critical in steel columns located in the higher stories of the building; a nonslender column at ambient conditions can transform to a slender section at elevated temperatures. This can induce temperature-induced local instability in the column and lead to an early onset of instability at member and structural levels.

This study proposes a concept for the development of a fireproof design code for the verification of dwellings susceptible to wildfire action. There are currently structural codes for the design of buildings when subjected to indoor fires, outside fires that grow on the facade of buildings, and even fires in an accident situation due to ignitions with hydrocarbons or transportation vehicles. All of these security verification specifications are described in EC1:1–2. The current regulation in Portugal uses safety criteria and risk categories that are for indoor fires, therefore is very conservative and may not present an economic fireproof design against the action of wildfires. The aim of this work is a straight verification based on natural temperature characteristic curves that simulate wildfire heat flow by convection, radiation, and the deposits of firebrands.

Experience from past earthquakes has demonstrated the need to account for design goals beyond safety, known as functional recovery objectives, in the interest of community resilience. Frameworks have been proposed in the literature to assess the post-earthquake functional recovery of a building, but without accounting for utility systems’ disruption, which may be a key contributor to determining when a building is functional. This paper integrates a previously proposed probabilistic method for estimating the post-earthquake restoration of critical utility services with an individual building's functional recovery assessment framework. The integration was performed by incorporating utilities into the building system fault trees embedded into a functional recovery framework for various building occupancies (residential and commercial office buildings). Once incorporated, the results are used to interrogate the functional recovery of a reinforced concrete building, and the recovery time results were presented for seven cases investigating contributing factors in the functional recovery results including the number of crews available for lifeline restoration, the effect of low-quality service on meeting tenant requirements for elevators, heating ventilation and air conditioning (HVAC), plumbing and electrical systems, consideration of fire watch, the effect of building seismic retrofit, as well as different cases of fragility functions for the lifeline systems. Results showed that utility systems’ disruption does not have a significant impact on the recoccupancy of a building because only one utility-dependent building system (fire suppression) is needed for the building's safety. Unlike reoccupancy, utility systems are significant for functional recovery, mainly at moderate hazard levels because, at these levels, lifeline networks could be damaged without significant building damage, such that the lifeline systems restoration governs. Buildings with more restrictive tenant requirements are more sensitive to tenant disruptions.

Communities depend on critical infrastructure systems to support their regular operations and future development. Destructive events, such as natural disasters, threaten to disrupt service to these systems and the communities they support. Strategies designed to reduce the impacts from disasters and other events are therefore an important consideration for community planning. At a regional level, coordination between communities supports the efficient use of resources for implementing disaster risk reduction (DRR) measures and completing post-disaster repairs to meet the needs of all residents. Coordination is challenging, however, due to the complexity of regional systems and competing stakeholder interests. This work presents a case study model of regional water, wastewater, and power systems, and demonstrates the effect of seismic hardening and increased resource availability on post-earthquake repair requirements and critical infrastructure recovery. Model results indicate that implementing DRR strategies can reduce required repair costs by over 40 percent and outage severity by approximately 50 percent for the studied sectors. Not all strategies are effective for all sectors and locations, however, so this work discusses the importance of comprehensive, coordinated, and accessible emergency planning activities to ensure that the needs of all residents are considered.

Despite efforts to end homelessness in the United States, student homelessness is gradually growing over the past decade. Homelessness creates physical and psychological disadvantages for students and often disrupts school access. Research suggests that students who experience prolonged dislocation and school disruption after a disaster are primarily from low-income households and under-resourced areas. This study develops a framework to predict post-disaster trajectories for kindergarten through high school (K-12) students faced with a major disaster; the framework includes an estimation on the households with children who recover and those who experience long-term homelessness. Using the National Center for Education Statistics school attendance boundaries, residential housing inventory, and U.S. Census data, the framework first identifies students within school boundaries and links schools to students to housing. The framework then estimates dislocation induced by the disaster scenario and tracks the stage of post-disaster housing for each dislocated student. The recovery of dislocated students is predicted using a multi-state Markov chain model, which captures the sequences that households transition through the four stages of post-disaster housing (i.e., emergency shelter, temporary shelter, temporary housing, and permanent housing) based on the social vulnerability of the household. Finally, the framework predicts the number of students experiencing long-term homelessness and maps the students back to their pre-disaster school. The proposed framework is exemplified for the case of Hurricane Matthew-induced flooding in Lumberton, North Carolina. Findings highlight the disparate outcomes households with children face after major disasters and can be used to aid decision-making to reduce future disaster impacts on students.