This project focused on developing computational strategies to enhance the design and resilience of structures subjected to multiple hazards, such as extreme wind and seismic events. By integrating innovations in machine learning, stochastic simulation, and advanced multi-fidelity frameworks, the research sought to improve how uncertainty is managed in structural assessments, thereby optimizing design processes. These improvements were aimed at ensuring both computational efficiency and high accuracy in simulations, addressing the complex challenges faced by structural engineers in designing systems that must withstand the dynamic forces resulting from natural hazards. Alongside the technological advancements, the project also placed significant emphasis on education and outreach. Efforts were made to engage students, particularly those from underserved populations, in STEM disciplines. Through specially designed units and hands-on research opportunities, high school and undergraduate students were introduced to fundamental engineering concepts, as well as the latest developments in wind engineering and risk mitigation. This educational component aimed to inspire future generations and encourage plurality in engineering fields.

Intellectual Merit: The intellectual contributions of this project lie in its pioneering advances in metamodeling and uncertainty propagation. By integrating techniques such as reduced order modeling and deep learning, the project resulted in the introduction of metamodeling schemes capable of achieving massive reductions in simulation times without sacrificing accuracy. These developments are crucial for modeling complex, nonlinear high-dimensional systems subject to the stochastic loads generated by natural hazards, providing insights previously unattainable with conventional methods. Furthermore, the project introduced multi-fidelity frameworks that significantly enhanced risk assessment capabilities by enabling both efficient and accurate estimation of the small failure probabilities associated with rare events. These frameworks optimally combined low- and high-fidelity models through advanced stratified sampling and metamodeling techniques, enabling more scalable and robust evaluations of wind and seismic risks. In addition, the project developed advanced multi-objective optimization strategies, balancing initial construction costs and potential future losses, thereby offering robust solutions to traditionally conflicting design objectives. These advances are particularly beneficial to performance-based engineering, where continuous optimization of costs, risks, and resilience is crucial.

Broader Impacts: The project had a profound impact not just on technical practices within the field of structural engineering but also on educational and industry standards. Educationally, it increased STEM engagement by providing innovative teaching units and substantial research opportunities geared towards high school and undergraduate students. Special efforts were made to include women and individuals from underserved populations, fostering a broad environment that cultivates a varied talent pool in engineering disciplines. These initiatives aim to inspire interest and build a strong foundation for future careers in technical fields. In terms of industry impact, the methodologies and findings from this project are shaping practices in performance-based wind engineering. The advanced tools and frameworks developed are being integrated into new software solutions used by industry professionals, transforming how structural engineers conduct risk assessments and model complex systems. This integration ensures safer and more cost-efficient construction practices, directly affecting how industry standards are set and maintained. Moreover, the project’s findings are increasingly being adopted by professional committees dedicated to advancing the codes and standards adopted by industry. This ensures that the academic innovations resulting from this project are directly translated into practical benefits for wider society. As a result, the project not only expanded the academic boundaries of structural engineering but also ensured its findings have a lasting impact on industry practices. Through these collective efforts, the project contributed significantly to the fields of structural resilience and safety, addressing critical challenges in structural modeling and optimization while laying a foundation for future research and practical applications. By merging academic theory with practical engineering needs, it has set the stage for lasting improvements in how complex design challenges are approached in both educational and professional contexts.

Last Modified: 02/11/2025
Modified by: Seymour M Spence