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1. Multi-hazard vulnerability modeling: an example of wind and rain vulnerability of mid/high-rise buildings during hurricane events

   Wei, Zhuoxuan; Pinelli, Jean-Paul; Gurley, Kurtis; Hamid, Shahid (May 2024, Wind and Structures)

   Severe natural multi-hazard events can cause damage to infrastructure and economic losses of billions of dollars. The challenges of modeling these losses include dependency between hazards, cause and sequence of loss, and lack of available data. This paper presents and explores multi-hazard loss modeling in the context of the combined wind and rain vulnerability of mid/high-rise buildings during hurricane events. A component-based probabilistic vulnerability model provides the framework to test and contrast two different approaches to treat the multi-hazards: In one, the wind and rain hazard models are both decoupled from the vulnerability model. In the other, only the wind hazard is decoupled, while the rain hazard model is embedded into the vulnerability model. The paper presents the mathematical and conceptual development of each approach, example outputs from each for the same scenario, and a discussion of weaknesses and strengths of each approach. 

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2. A novel framework to study community-level social and physical impacts of hurricane-induced winds through synthetic scenario analysis

   https://doi.org/10.3389/fbuil.2023.1005264  

   Mazumder, Ram Krishna; Enderami, S. Amin; Sutley, Elaina J. (February 2023, Frontiers in Built Environment)

   Strong hurricane winds often cause severe infrastructure damage and pose social and economic consequences in coastal communities. In the context of community resilience planning, estimating such impacts can facilitate developing more risk-informed mitigation plans in the community of interest. This study presents a new framework for synthetically simulating scenario-hurricane winds using a parametric wind field model for predicting community-level building damage, direct economic loss, and social consequences. The proposed synthetic scenario approach uses historical hurricane data and adjusts its original trajectory to create synthetic change scenarios and estimates peak gust wind speed at the location of each building. In this research, a stochastic damage simulation algorithm is applied to assess the buildings’ physical damage. The algorithm assigns a damage level to each building using the corresponding damage-based fragility functions, predicted maximum gust speed at the building’s location, and a randomly generated number. The monetary loss to the building inventory due to its physical damage is determined using FEMA’s direct loss ratios and buildings’ replacement costs considering uncertainty. To assess the social impacts of the physical damage exposure, three likely post-disaster social disruptions are measured, including household dislocation, employment disruption, and school closures. The framework is demonstrated by its application to the hurricane-prone community of Onslow County, North Carolina. The novel contribution of the developed framework, aside from the introduced approach for spatial predicting hurricane-induced wind hazards, is its ability to illuminate some aspects of the social consequences of substantial physical damages to the building inventory in a coastal community due to the hurricane-induced winds. These advancements enable community planners and decision-makers to make more risk-informed decisions for improving coastal community resilience. 

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3. Multi‐hazard probabilistic risk assessment and equitable multi‐objective optimization of building retrofit strategies in hurricane‐vulnerable communities

   https://doi.org/10.1111/mice.13445  

   Braik, Abdullah M; Gupta, Himadri Sen; Koliou, Maria; González, Andrés D (June 2025, Computer-Aided Civil and Infrastructure Engineering)

   Abstract Coastal communities are increasingly vulnerable to hurricanes, which cause billions of dollars in damage annually through wind, storm surge, and flooding. Mitigation efforts are essential to reduce these impacts but face significant challenges, including uncertainties in hazard prediction, damage estimation, and recovery costs. Resource constraints and the disproportionate burden borne by socioeconomically vulnerable groups further complicate retrofitting strategies. This study presents a probabilistic methodology to assess and mitigate hurricane risks by integrating hazard analysis, building fragility, and economic loss assessment. The methodology prioritizes retrofitting strategies using a risk‐informed, equity‐focused approach. Multi‐objective optimization balances cost‐effectiveness and risk reduction while promoting fair resource allocation among socioeconomic groups. The novelty of this study lies in its direct integration of equity as an objective in resource allocation through multi‐objective optimization, its comprehensive consideration of multi‐hazard risks, its inclusion of both direct and indirect losses in cost assessments, and its use of probabilistic hazard analysis to incorporate varying time horizons. A case study of the Galveston testbed demonstrates the methodology's potential to minimize damage and foster equitable resilience. Analysis of budget scenarios and trade‐offs between cost and equity underscores the importance of comprehensive loss assessments and equity considerations in mitigation and resilience planning. Key findings highlight the varied effectiveness of retrofitting strategies across different budgets and time horizons, the necessity of addressing both direct and indirect losses, and the importance of multi‐hazard considerations for accurate risk assessments. Multi‐objective optimization underscores that equitable solutions are achievable even under constrained budgets. Beyond a certain point, achieving equity does not necessarily increase expected losses, demonstrating that more equitable solutions can be implemented without compromising overall cost‐effectiveness. 

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4. A Unified Framework for Post-disaster Hazard and Structural Assessment Data Collection Across Hazards and Infrastructure Typologies

   Alam, Mohammad; Kijewski-Correa, Tracy; Roueche, David; Mosalam, Khalid; Prevatt, David; Robertson, Ian (May 2025, Frontiers in built environment)

   Post-disaster field observations of the built environment are critical for advancing fundamental research that links hazard data to structural performance, cascading community impacts, and the development of effective mitigation strategies. Yet, data collection remain fragmented across hazard types and infrastructure systems due to varying objectives, methodologies, protocols, and standards among investigators and organizations. To address this, a Unified Assessment Framework has been developed for standardized post-disaster hazard and structural assessment data and metadata collection across multiple natural hazards (earthquake, windstorm, coastal events) and infrastructure typologies. The framework encompasses a tiered performance assessment structure with increasing rigor and fidelity levels: Basic Assessment (BA), Load Path Assessment (LPA), and Detailed Component Assessment (DCA). The framework has been implemented as an open-access mobile application, the Structural Extreme Events Reconnaissance (StEER) Network’s StEER Unified App, hosted on Fulcrum data collection platform . Along with unification of data fields, preliminary mapping rules were developed to map out existing hazard-specific damage rating scales (e.g., wind, surge/flooding, rainwater ingress) to the European Macroseismic Scale (EMS-98) compatible unified damage scale, enabling consolidation of global damage ratings into a common data field, facilitating the unification of multiple hazards within a single app. In the mapping of damage ratings, overarching level definitions were retained (e.g., slight, moderate, severe damage) while customizing the specific descriptors to reflect hazard-specific damage mechanisms. Two use cases are presented to demonstrate the application of this framework through the StEER Unified App: a supervised pilot after the 2022 Hurricane Ian, Florida and an unsupervised deployment for the 2023 Turkey earthquake sequence. These deployments illustrate the framework’s flexibility and scalability, validate the feasibility of standardized assessments, and offer insights into how data quality is influenced by assessor pre-deployment training and assessment tier—particularly for complex tasks such as load path evaluation. This work advances the field by providing a scalable, standardized, and hazard-agnostic approach to structural field reconnaissance. The open-access framework and app support real-time deployments and enable integration of legacy datasets into a unified platform—laying the foundation for longitudinal analyses, cross-hazard comparisons, and expanded data reuse in the Natural Hazards Engineering community. 

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5. Passive acoustic damage detection of structural cavities using flow-induced acoustic excitations

   https://doi.org/10.1177/1475921719860389  

   Beale, Christopher; Willis, David_J; Niezrecki, Christopher; Inalpolat, Murat (July 2019, Structural Health Monitoring)

   Cavities with different geometries represent the internal volumes of various engineering applications such as cabins of passenger cars, fuselages and wings of aircraft, and internal compartments of wind turbine blades. Transmissibility of acoustic excitation to and from these cavities is affected by material and cross-sectional properties of the structural cavity, as well as potential damage incurred. A new structural damage detection methodology that relies on the detectability of the changes in acoustic transmissibility across the boundaries of structural cavities is proposed. The methodology is described with a specific focus on the passive damage detection approach applied to cavity internal acoustic pressure responses under external flow-induced acoustic excitations. The approach is realized through a test plan that considers a wind turbine blade section subject to various damage types, severity levels, and locations, as well as wind speeds tested in a subsonic wind tunnel. A number of statistics-based metrics, including power spectral density estimates, band power differences from a known baseline, and the sum of absolute difference, were used to detect damage. The results obtained from the test campaign indicated that the passive acoustic damage detection approach was able to detect all considered hole-type damages as small as 0.32 cm in diameter and crack-type damages 1.27 cm in length. In general, the ability to distinguish damage from the baseline state improved as the damage increased in severity. Damage type, damage location, and flow speed influenced the ability to detect damage, but were not significant enough to prevent detection. This article serves as an overall proof of concept of the passive-based damage detection approach using flow-induced acoustic excitations on structural cavities of a wind turbine blade. The laboratory-scale results reveal that acoustic-based monitoring has great potential to be used as a new structural health monitoring technique for utility-scale wind turbine blades. 

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