Postdoctoral Scholar University of Houston
Integrated Spatiotemporal Assessment of Infrastructure Resilience and Community Vulnerability in Houston
Co-Author: Abigail L. Beck (University of Houston)
Abstract: The 311 service request system offers high resolution spatiotemporal data for monitoring urban infrastructure performance and civic service demand. This study examines 311 requests in Harris County, Houston, from 2013 to 2023 at the census tract level to explore correlations between infrastructure repair demand and community vulnerability indices under three scenarios: normal operations, extreme weather events, and combined conditions. Request volumes are normalized by area to ensure that spatial patterns reflect genuine infrastructure failure densities rather than population distribution. Impact assessments cover ten major disasters, including the 2015 and 2016 Memorial Day and Halloween Floods, the 2016 Tax Day Flood, Hurricane Harvey (2017), Tropical Storms Imelda (2019) and Beta (2020), Winter Storm Uri (2021), Hurricane Nicholas (2021), and the 2023 Tornadoes. Three priority 311 categories including Solid Waste Management, Streets and Traffic, and Water and Wastewater are analyzed in detail. These data are integrated with the Social Vulnerability Index (SVI) along with supplementary resilience indicators, specifically the Houston-Resilience Indicators for Communities (H-RIC), to assess the interplay between community vulnerability, resilience profiles, and systemic infrastructure performance. Advanced geostatistical methods are applied: Global Moran’s I measures overall spatial autocorrelation, while univariate and bivariate Local Indicators of Spatial Association (LISA) identify hotspots and significant spatial correlations between service demand and vulnerability indices. This framework quantifies disparities across operational conditions, supports resource allocation, and enhances predictive modeling of infrastructure performance. By integrating 311 dynamics with actual damage and outage records, the study strengthens resilience monitoring and informs proactive urban infrastructure management.
Associate Professor American University of Beirut
Seismic Risk Assessment of the Rafik Hariri University Hospital Neighborhood in Beirut and Resulting Patient Demands
Co-Author: Mohamed Khoudari (American University of Beirut - Lebanon) - Presenting
Abstract: While Lebanon is prone to major earthquakes, most pre-1990s structures were not seismically designed, making them vulnerable to severe damage and human and financial losses. After major seismic events, healthcare facilities witness a drastic increase in demand, playing a major role in determining community resilience. This study focuses on the Rafik Hariri University Hospital (RHUH), a major public hospital in Beirut, Lebanon. It assesses seismic losses and expected emergency services demand in the first 24 hours following a magnitude 7 earthquake on the Yammouneh fault. More specifically, the study evaluates structural damage and resulting debris, injuries, and fatalities from different earthquake realizations, then performs traffic simulations to calculate expected patient arrival rates at RHUH, accounting for debris effects on transportation. The Regional Resilience Determination (R2D) tool developed by SimCenter is used, interfaced with Python and ArcGIS codes. For the 84th-percentile realization, nearly 50% of 3,408 buildings would be completely (432) or severely (1,210) damaged, producing almost 380,000 m3 of debris blocking 59 of 1,403 road segments. Among 113,191 people, estimated casualties include 44 fatalities or mortal injuries, 23 life-threatening injuries, 216 moderate injuries requiring hospitalization, and 996 minor injuries. RHUH is expected to receive 70% of these injuries: 78 in the first 5 hours, 128 in 10 hours, and 198 in 24 hours (excluding minor injuries). This study can advance earthquake preparedness in Lebanon by offering authorities a methodology to support emergency response planning and infrastructure improvements, enhancing seismic resilience and reducing human and economic losses in future seismic events.
PhD Student University of Kansas
Advancing a new paradigm for prioritizing residential buildings in community resilience using testbed simulations
Co-Author: Elaina Sutley (University of Kansas)
Abstract: Residential buildings remain among the most vulnerable components of the built environment under tornado hazard, yet current tornado load provisions explicitly exclude them. One reason for this is because the small footprint area of residential buildings and the low strike probability for any individual footprint provide inconsistent reliabilities with other codified loads. At the same time, empirical studies of events such as the 2011 Joplin Tornado show that damage, population dislocation, and rebuilding trajectories are highly clustered in space and time, shaped by neighborhood socio-economic characteristics, social ties, and shared infrastructure. These community-scale patterns are not captured when buildings are initially designed or when benefit-cost evaluations focus on isolated buildings.
This study introduces a new paradigm for evaluating “effective design area” for residential buildings that explicitly accounts for clustered geospatial, social, and infrastructural interdependencies. We propose and compare several candidate definitions: (1) block-group effective areas; (2) infrastructure-dependent effective areas; (3) damage-state clustering effective areas, defined by spatial clusters of homes in severe damage states; (4) social-ties effective areas, representing neighborhoods with strong indicators of place attachment; and (5) National Weather Service warning polygons as an operationally relevant reference.
Using the IN-CORE simulation environment and Joplin testbed, community-scale performance metrics, including number of displaced households, spatial concentration of severe damage, and losses, are estimated and compared among different effective design areas. The findings from this study demonstrate how broader definitions of design relevance beyond an isolated structural system can inform housing policy, shelter planning, and resilience investments.
PhD Student University of California, Los Angeles
Designing Earthquake Reciprocal Exchanges with Retrofit-Informed Risk Reduction
Co-Author: Henry Burton (UCLA)
Abstract: Limited uptake of earthquake insurance and growing stress in traditional insurance markets motivate the exploration of alternative, community-based risk transfer mechanisms. This study investigates the potential of reciprocal exchanges as a transparent and analytically grounded framework for managing earthquake risk, with particular emphasis on how physical risk-reduction measures can enhance exchange performance. We focus on the integration of seismic retrofitting and reciprocal exchange design as a coupled strategy for improving long-term affordability, stability, and resilience.
A modeling framework is developed to examine the dynamics of a reciprocal exchange using a pilot study of single-family residential buildings with cripple-wall vulnerability in Los Angeles. Stochastic earthquake loss modeling is combined with an explicit formulation of exchange operations, including premium contributions, surplus accumulation, claims payments, and participation in external insurance markets. Parametric sensitivity analyses are conducted to evaluate the influence of key design choices, including insured limits, deductibles, exchange premium rates, and the role of external market coverage.
The results demonstrate that seismic retrofitting can materially alter exchange dynamics by reducing loss frequency and severity, accelerating surplus growth, and improving the exchange’s capacity for partial self-insurance over time. More broadly, the findings highlight how integrating retrofit-based risk reduction with reciprocal exchange design can support more efficient, scalable, and transparent approaches to community-level earthquake risk management.
PhD Student Stanford University
Evaluating San Francisco’s Soft-Story Retrofit Program: A Stakeholder-Engaged Regional Risk Assessment
Co-Authors: Adam Zsarnoczay (Stanford University) and Gregory Deierlein (Stanford University)
Abstract: This study evaluates the effectiveness of San Francisco's Mandatory Soft-Story Retrofit Ordinance in reducing seismic risk. Since implementation, nearly 5,000 soft-story wood-framed buildings have been seismically retrofitted, representing one of the nation's most comprehensive seismic risk reduction initiatives. Conducted in partnership with San Francisco's Office of Resilience and Capital Planning, this stakeholder-engaged research employs SimCenter computational tools to perform high-resolution regional seismic risk simulations aimed at quantifying the impacts of this ordinance. Detailed building inventories were developed by merging publicly available datasets and supplemented with BRAILS++, while representative building archetypes and corresponding seismic fragility functions were adapted from existing literature on wood-frame buildings (FEMA P-807-1). Scenario-based seismic risk simulations were then conducted via R2D, utilizing Pelicun’s custom fragility function feature. Results extend beyond traditional collapse risk metrics to evaluate real-world policy impacts on San Francisco residents. The analysis quantifies reductions in damages, recovery time, and post-earthquake human displacement, examining differential effects on neighborhood demographics, low-income populations, and other vulnerable communities. By demonstrating how seismic retrofit programs protect both buildings and people, this study aims to provide evidence-based guidance for future urban resilience policy. This study is the first stage of a broader collaboration between Stanford University researchers and the City of San Francisco to leverage advanced computational modeling for informed disaster risk reduction decision-making.
Postdoctoral Scholar University of California, Berkeley
Multi-Hazard Resilience Assessment of Coastal Communities
Co-Author: Eyitayo Opabola (UC Berkeley)
Abstract: The United States’ coastal communities are increasingly exposed to extreme wind and flooding hazards. Although these hazards can occur independently, climate change is altering their intensity and frequency in ways that increase the likelihood of compound wind–flood events and amplify community-wide impacts. This study presents an integrated framework for multi-hazard resilience assessment of coastal communities under climate change. The framework generates climate-informed multi-hazard maps of wind speed and inundation depth at specified return periods for future time horizons under different climate scenarios, quantifies resulting community-level building damage and direct economic loss, and evaluates recovery trajectories using time-dependent restoration modeling and resilience metrics. The proposed framework enables climate-informed, community-level multi-hazard resilience assessment by linking future wind and inundation scenarios to a coastal community’s potential damage, loss, and recovery performance, while supporting consistent comparison between single-hazard and compound-hazard outcomes. A case study is conducted for a marginalized coastal community near San Francisco, California. Results show how climate change-driven shifts in hazard intensity and dependence influence spatial patterns of damage and loss and reshape recovery trajectories over time. The results provide actionable insights to prioritize mitigation measures, guide adaptation planning, and target resilience investments in coastal communities.