This National Science Foundation (NSF) Engineering grant award, with the Catalog of Federal Domestic Assistance (CFDA) number 47.041, provides $607,802 in funding from August 1, 2025 to July 31, 2030 to the University of Nevada, Reno to develop a physics-informed machine learning framework for modeling the dynamic response of geostructural systems under seismic loading. The key objectives are to: (1) develop scalable machine learning algorithms for accurately modeling the dynamic response of geostructural systems to seismic wave propagation, (2) develop approaches to accommodate uncertainties in risk assessment tasks, and (3) validate the framework and assess its effectiveness using experimental data. This research aims to enable rapid and reliable seismic response predictions, promote integration of high-fidelity data into risk assessment workflows, and enhance earthquake engineering and resilience strategies for geostructural systems. The project also includes complementary educational initiatives to improve scientific machine learning literacy and train a new generation of engineers.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $607.8k | 4/14/25 |