CAREER: Integrating Structural, Social, and Preservation Factors in Tornado Damage and Recovery Models

About This Grant

This Faculty Early Career Development (CAREER) award will fund research that intends to develop an interdisciplinary framework to improve the resilience of unreinforced masonry buildings in tornado-prone areas of the United States. Unreinforced masonry structures, prevalent in rural town centers and inner-city neighborhoods, play an important role in preserving cultural identity and contributing to social and economic resilience; however, their vulnerability to tornadoes is not well understood or modeled. Through integrating engineering, social science, and preservation perspectives, this research aims to advance the science behind vulnerability and recovery models for unreinforced masonry buildings. The project intends to enhance community resilience, preserve cultural heritage, and support sustainable development in historically underserved areas. A key component of this project is its educational program, which will cultivate a new generation of professionals equipped with interdisciplinary skills to address disaster resilience and recovery challenges in communities dense with older, unreinforced masonry structures. The educational program will include new undergraduate and graduate coursework, hands-on research opportunities for students, workforce development programs, and community co-learning experiences. By bridging the gap between academic research and practical application, these educational activities will prepare students, professionals, and community members to tackle real-world challenges in disaster preparedness and recovery. This award will contribute to NSF's role in the National Windstorm Impact Reduction Program (NWIRP). This research intends to develop a framework for understanding and modeling the complex dynamics of older unreinforced masonry buildings during tornado events and recovery. By identifying and operationalizing key structural, social, and preservation features to create more accurate predictive models for damage and recovery, this project intends to advance both pre-disaster mitigation strategies and post-disaster recovery efforts. The research methodology will include (1) collecting and analyzing quantitative and qualitative data from tornado-affected communities using remote sensing techniques, in-situ surveys, and socio-economic assessments; (2) performing feature importance analysis through machine learning algorithms such as random forests and gradient boosting; and (3) developing updated fragility curves using Bayesian statistical methods and Monte Carlo simulations. The project outcomes will include refined damage and recovery models for unreinforced masonry structures, practitioner guides, and community tip sheets, thus translating research findings into actionable resources for disaster preparedness and recovery planning. This approach intends to provide communities, policymakers, and practitioners with valuable tools to enhance the recovery and resilience of unreinforced masonry structures in tornado-prone areas. By providing the first interdisciplinary framework for assessing and enhancing the resilience of unreinforced masonry structures in tornado-prone areas, this research will advance the field of disaster resilience, transforming how communities approach disaster preparedness, mitigation, and recovery while preserving irreplaceable cultural heritage. Project data will be archived and made publicly available in the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Data Depot (https://www.DesignSafe-ci.org). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.