Performance-Based Wind Engineering: Knowledge and Computational Modeling Advances for Collapse Characterization

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Each year, extreme windstorms cause significant economic and societal losses in the United States. Current performance-based wind engineering (PBWE) methodologies do not provide a means to characterize the collapse performance of engineered building systems subject to extreme winds. This not only limits the design innovation necessary for achieving building systems that mitigate these losses at reduced costs and environmental impacts, but also hinders the development of the next generation of guidelines and standards for PBWE that would lead to the advancement of national prosperity and welfare through better performing building infrastructure. This award will provide the necessary advances in knowledge and modeling to address this fundamental gap through 1) creation of new knowledge on the probabilistic collapse capacity of typical engineered building systems subject to extreme winds, 2) creation of practical and validated methodologies for the rapid probabilistic collapse assessment of engineered building systems, and 3) technology transfer to the wind engineering practicing community. Impact on graduate and undergraduate education will be created through integrated research activities that foster greater participation of underrepresented groups by leveraging multiple programs at the University of Michigan. The computational methodologies resulting from this award will be shared through the National Science Foundation-supported Natural Hazards Engineering Research Infrastructure (NHERI) Computational Modeling and Simulation Center (https://simcenter.designsafe-ci.org/). Project data will be archived and made publicly available in NHERI’s Data Depot (https://www.designsafe-ci.org). This research will contribute to NSF's role in the National Windstorm Impact Reduction Program.This award will create a holistic collapse modeling environment for the structural and envelope systems of engineered buildings subject to extreme winds. A new class of multivariate stochastic pressure models will characterize the extreme loads associated with both synoptic and hurricane events. The damage susceptibility of the building system will be captured through coupling high-fidelity finite element modeling with progressive and interdependent multi-demand fragility analysis. Optimal stratified sampling schemes will enable rapid estimation of probabilities associated with rare events, e.g., system collapse, over a full range of wind load and modeling uncertainties. By leveraging the high-performance computing infrastructure of NHERI, fundamental knowledge on the collapse fragility of typical building systems will be created through the collapse analysis of a suite of archetype buildings specifically identified for the advancement of PBWE. This knowledge will provide the foundation for not only the development of practical and validated probabilistic methodologies for the holistic collapse assessment of engineered building systems, but also the advancement of guidelines and standards for PBWE.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.