Communicating risks and mitigation benefits associated with natural hazards such as wind to the general public is challenging given the location-dependency of parameters and the complexity of the problem. Web tools play a crucial role in educating residents, decision-makers, and stakeholders regarding potential wind hazard losses to, for example, residential buildings.
However, a notable gap exists on the practical incorporation of mitigation actions within these tools. This gap hampers the collective awareness and understanding among stakeholders, communities, and citizens regarding the tangible advantages of mitigation strategies in reducing wind-related risks. Furthermore, there exists a need to elucidate the functionality and objectives of these tools in a more accessible manner. This study aims to present and outline the wind risk and mitigation calculator tool (WRMCT) within the Hazardaware platform, which is an address-based risk assessment tool. This tool, developed for 196 counties in the Gulf of Mexico coastal area, facilitates users' education of potential risks and benefits associated with mitigation strategies. WRMCT enables users to access location-specific wind risk and interactively suggests potential mitigation actions along with economic savings to support informed decisions and residential risk reduction. WRMCT intends to enhance users’ ability to make informed decisions, take proactive measures in mitigating wind hazards, and contribute to the development of resilient, residential communities.
Past earthquakes have shown that cracking affects post-earthquake functionality and accounted for huge repair costs for reinforced concrete (RC) wall buildings, even though the code-compliant seismic design prevents collapse. Engineers should know the maximum residual flexural crack width and volume of repair material needed for the flexural cracks to determine the damage degree and the repair cost. This paper presents the experimental campaign on four RC slender walls that investigated the effect of confining reinforcement and thickness of the wall on flexural crack parameters under quasi-static reversed cyclic loading. The width of all flexural cracks was measured when reaching each cycle peak drift and when unloading to zero lateral loads. Crack widths at peak and residual states increased with increasing peak drift. Based on the experimental observations, it was found that the maximum residual crack width is obtained as a simple function of the extreme tension fiber elongation of the wall tensile fiber within error. In addition, this paper outlines methods to calculate the volume of repair material for flexural cracks from the extreme tension fiber elongation of the wall. With the fundamental rules found from the experiment in this paper, it will become possible to obtain the maximum crack width and the volume of repair material from simple numerical analysis tools such as a multi-spring line element model.
This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters. The work is founded on the classic theoretic framework that system resilience is defined in multiple dimensions for a constructed system. Consequentially, system resilience can lose its parametric form as a random variable, falling into the realm of nonparametric statistics. With this nonparametric shift, traditional distribution-based statistics are ineffective in characterizing the migration of system resilience due to the variation of system parameters. Three statistical tools are proposed under the nonparametric statistical resilience analysis (npSRA) framework, including nonparametric copula-based sensitivity analysis, two-sample resilience test analysis, and a novel tool for resilience attenuation analysis. To demonstrate the use of this framework, we focus on electric distribution systems, commonly found in many urban, suburban, and rural areas and vulnerable to tropical storms. A novel procedure for considering resourcefulness parameters in the socioeconomic space is proposed. Numerical results reveal the complex statistical relations between the distributions of system resilience, physical aging, and socioeconomic parameters for the power distribution system. The proposed resilience distance computing and resilience attenuation analysis further suggests two proper nonparametric distance metrics, the Earth Moving Distance (EMD) metric and the Cramévon Mises (CVM) metric, for characterizing the migration of system resilience for electric distribution systems.
The community's resilience in the face of natural hazards relies heavily on the rapid and efficient restoration of electric power networks, which plays a critical role in emergency response, economic recovery, and the functionality of essential lifeline and social infrastructure systems. Leveraging the recent data revolution, the digital twin (DT) concept emerges as a promising tool to enhance the effectiveness of post-disaster recovery efforts. This paper introduces a novel framework for post-hurricane electric power restoration using a hybrid DT approach that combines physics-based and data-driven models by utilizing a dynamic Bayesian network. By capturing the complexities of power system dynamics and incorporating the road network's influence, the framework offers a comprehensive methodology to guide real-time power restoration efforts in post-disaster scenarios. A discrete event simulation is conducted to demonstrate the proposed framework's efficacy. The study showcases how the electric power restoration DT can be monitored and updated in real-time, reflecting changing conditions and facilitating adaptive decision-making. Furthermore, it demonstrates the framework's flexibility to allow decision-makers to prioritize essential, residential, and business facilities and compare different restoration plans and their potential effect on the community.
The swift recuperation of communities following natural hazards heavily relies on the efficiency of transportation systems, facilitating the timely delivery of vital resources and manpower to reconstruction sites. This paper delves into the pivotal role of transportation systems in aiding the recovery of built environments, proposing an evaluative metric that correlates transportation capacity with the speed of post-earthquake recovery. Focusing on optimizing urban population capacity in the aftermath of earthquakes, the study comprehensively examines the impact of pre-earthquake measures such as enhancing building or bridge seismic performance on post-earthquake urban population capacity. The methodology is demonstrated through an analysis of Beijing’s transportation system, elucidating how enhancements to transportation infrastructure fortify the resilience of built environments. Additionally, the concept of a resource supply rate is introduced to gauge the level of logistical support available after an earthquake. This rate tends to decrease when transportation damage is significant or when the demands for repairs overwhelm available resources, indicating a need for retrofitting. Through sensitivity analysis, this study explores how investments in the built environment or logistical systems can increase the resource supply rate, thereby contributing to more resilient urban areas in the face of seismic challenges.