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1. A modified approximate dynamic programming algorithm for community-level food security following disasters

   Nozhati, S. ; Sarkale, Y. ; Ellingwood, B. R. ; Chong, E. K. ; Mahmoud, H. ( June 2018 , 2018 9th International Congress on Environmental Modelling and Software (iEMSs))

   In the aftermath of an extreme natural hazard, community residents must have access to functioning food retailers to maintain food security. Food security is dependent on supporting critical infrastructure systems, including electricity, potable water, and transportation. An understanding of the response of such interdependent networks and the process of post-disaster recovery is the cornerstone of an efficient emergency management plan. In this study, the interconnectedness among different critical facilities, such as electrical power networks, water networks, highway bridges, and food retailers, is modeled. The study considers various sources of uncertainty and complexity in the recovery process of a community to capture the stochastic behavior of the spatially distributed infrastructure systems. The study utilizes an approximate dynamic programming (ADP) framework to allocate resources to restore infrastructure components efficiently. The proposed ADP scheme enables us to identify near-optimal restoration decisions at the community level. Furthermore, we employ a simulated annealing (SA) algorithm to complement the proposed ADP framework and to identify near-optimal actions accurately. In the sequel, we use the City of Gilroy, California, USA to illustrate the applicability of the proposed methodology following a severe earthquake. The approach can be implemented efficiently to identify practical policy interventions to hasten recovery of food systems and to reduce adverse food-insecurity impacts for other hazards and communities. 

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2. Informally-Constructed houses under Typhoon:Building Capacity for Safer Post-disaster Shelter: Leveraging Local Understanding and Advanced Engineering Assessments

   https://doi.org/10.17603/ds2-d9g9-2d62  

   Venable, Casie ; Liel, Abbie ; Kijewski-Correa, Tracy ; Javernick-Will, Amy ( January 2024 , Designsafe-CI)

   Although organizations build housing in resource-limited contexts after typhoons and other disasters that is intended to be safer than what existed previously, the performance of these houses in future typhoons—and the factors influencing performance—are unknown. This study develops a component-level, performance-based wind engineering assessment framework and evaluates the wind performance of twelve semi-engineered post-disaster housing designs, representing thousands of houses that were constructed in the Philippines after Typhoon Yolanda. We found that roof panel loss likely occurs first for most designs, at wind speeds equivalent to a category 2 hurricane/signal 3 typhoon. Roof shape determines whether this loss is caused by failure at the panel-fastener interface or purlin-to-truss connection. However, houses with wooden frames and woven bamboo walls may also experience catastrophic racking failures at wind speeds equivalent to signal 2 or 3 typhoons, a situation exacerbated by strengthening the roof. Results also show that wind performance varied with roof shape, component spacing, panel thickness, eave length and connection between purlin and truss. Organizations can use these results to improve housing performance, taking specific care to increase wall capacity. This framework can be expanded to assess housing performance in other resource-limited contexts.There is an urgent need to improve community capacity to recover more effectively after disasters through safer design and construction practices. To do this, training programs need to foster an improved understanding of shelter design and construction to withstand future wind and earthquake events. This project analyzed informal builders’ perceptions of housing safety in Puerto Rico (responding to 2017's Hurricane Maria and the 2019-2020 earthquake swarm) and homeowner’s perceptions of housing safety in Philippines (responding to 2013's Typhoon Haiyan and 2017's Ormoc earthquake) to: (1) assess local understanding of shelter safety in multiple hazards, including causal factors influencing this understanding, through a household survey in the Philippines and a survey to informal contractors in Puerto Rico; (2) assess the expected performance of various post-disaster shelter typologies to quantify safety during future earthquake and wind events using performance-based engineering methods, developing a rapid screening tool that can be used in design or evaluation; (3) identify conflicts between perceived and assessed safety of shelter, and why these conflicts exist, by comparing engineering assessments with local perceptions; and (4) create a communication design for organizations assisting with training for safer housing construction. 

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3. Topological surrogates for computationally efficient seismic robustness optimization of water pipe networks

   https://doi.org/10.1111/mice.12566  

   Pudasaini, Binaya ; Shahandashti, Mohsen ( May 2020 , Computer-Aided Civil and Infrastructure Engineering)

   The criticality of seismic robustness of the water pipe networks cannot be overstated. Current methodologies for optimizing seismic robustness of city‐scale water pipe networks are scarce. A very few studies that can be found are also prone to long optimization runtimes due to the requirement of repeated hydraulic analysis. Hence, there is a critical need for the identification of computationally efficient surrogate optimization methods for maximizing seismic robustness of water pipe networks. To address this need, this research was conducted to identify, for the first time, computationally efficient topological surrogates for hydraulic simulation‐based optimization. The computational efficiency of surrogate optimization was measured in terms of solution quality (i.e., post‐earthquake serviceability) and computational runtime. Ten different topological connectivity metrics were evaluated out of which five were considered computationally infeasible due to their prohibitive optimization runtime. Five remaining metrics were then used to formulate five surrogate objective functions for seismic robustness of water pipe networks. Each of these functions was optimized using a simulated annealing‐based algorithm. Application of the proposed approach to city‐level benchmark networks helped to identify two metrics out of ten that offered a substantial reduction in optimization runtime with a minimal loss in solution quality. These findings will be highly valuable to water distribution network managers for identifying economical rehabilitation policies for enhancing the seismic robustness at a city‐scale within a reasonable amount of time.

    

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4. Quantifying the Interdependency Strength Across Critical Infrastructure Systems Using A Dynamic Network Flow Redistribution Model.

   Wang, Y. ; Yu, J. ; Baroud, H. ( July 2020 , Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference.)

   Baraldi, P. ; null ; Zio, E. (Ed.)

   Critical infrastructure networks are becoming increasingly interdependent which adversely impacts their performance through the cascading effect of initial failures. Failing to account for these complex interactions could lead to an underestimation of the vulnerability of interdependent critical infrastructure (ICI). The goal of this research is to assess how important interdependent links are by evaluating the interdependency strength using a dynamic network flow redistribution model which accounts for the dynamic and uncertain aspects of interdependencies. Specifically, a vulnerability analysis is performed considering two scenarios, one with interdependent links and the other without interdependent links. The initial failure is set to be the same under both scenarios. Cascading failure is modeled through a flow redistribution until the entire system reaches a stable state in which cascading failure no longer occurs. The unmet demand of the networks at the stable state over the initial demand is defined as the vulnerability. The difference between the vulnerability of each network under these two scenarios is used as the metric to quantify interdependency strength. A case study of a real power-water-gas system subject to earthquake risk is conducted to illustrate the proposed method. Uncertainty is incorporated by considering failure probability using Monte Carlo simulation. By varying the location and magnitude of earthquake disruptions, we show that interdependency strength is determined not only by the topology and flow of ICIs but also the characteristics of the disruptions. This compound system-disruption effect on interdependency strength can inform the design, assessment, and restoration of ICIs. 

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5. Characterizing equitable access to grocery stores during disasters using location-based data

   https://doi.org/10.1038/s41598-022-23532-y  

   Esmalian, Amir ; Coleman, Natalie ; Yuan, Faxi ; Xiao, Xin ; Mostafavi, Ali ( December 2022 , Scientific Reports)

   Abstract Natural hazards cause disruptions in access to critical facilities, such as grocery stores, impeding residents’ ability to prepare for and cope with hardships during the disaster and recovery; however, disrupted access to critical facilities is not equal for all residents of a community. In this study, we examine disparate access to grocery stores in the context of the 2017 Hurricane Harvey in Harris County, Texas. We utilized high-resolution location-based datasets in implementing spatial network analysis and dynamic clustering techniques to uncover the overall disparate access to grocery stores for socially vulnerable populations during different phases of the disaster. Three access indicators are examined using network-centric measures: number of unique stores visited, average trip time to stores, and average distance to stores. These access indicators help us capture three dimensions of access: redundancy , rapidity , and proximity . The findings show the insufficiency of focusing merely on the distributional factors, such as location in a food desert and number of facilities, to capture the disparities in access, especially during the preparation and impact/short-term recovery periods. Furthermore, the characterization of access by considering combinations of access indicators reveals that flooding disproportionally affects socially vulnerable populations. High-income areas have better access during the preparation period as they are able to visit a greater number of stores and commute farther distances to obtain supplies. The conclusions of this study have important implications for urban development (facility distribution), emergency management, and resource allocation by identifying areas most vulnerable to disproportionate access impacts using more equity-focused and data-driven approaches. 

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