This National Science Foundation (NSF) Geosciences Program (CFDA 47.050) Project Grant award of $249,272, effective January 1, 2026 through December 31, 2028, supports the development of machine learning techniques to generate realistic, synthetic ground motion simulations for studying large earthquakes. The project, conducted by the University of Nevada, Reno (UNR), aims to create a physics-based, parametric surrogate model called Operator Inference (OPINF) that can produce seismic ground motion waveforms much faster than traditional methods. This will enable geologists to efficiently study the characteristics of large, infrequent earthquakes and assess related hazards in California and Nevada. The research outputs, including open-source software, will be made publicly available, and educational resources will be created to train future earthquake scientists and increase public awareness about earthquake safety procedures. No sub-awards are planned for this project.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $249.3k | 7/14/25 |