CAREER: Physics-Informed Deep Learning for Understanding Earthquake Slip Complexity — NSF Award to University of Oregon Eugene (OR
What it is about one fault that causes it to slip suddenly, unleashing catastrophic earthquakes, while another just creeps along steadily or produces smaller, more frequent earthquakes? This is difficult to assess because faults cannot be directly observed at depths where earthquakes start, typically 5 to 15 miles belo
| Award title | CAREER: Physics-Informed Deep Learning for Understanding Earthquake Slip Complexity |
|---|---|
| Award ID | 2339996 |
| Awardee | University of Oregon Eugene |
| City | EUGENE |
| State | OR |
| Amount obligated | $614,616 |
| Principal investigator | Brittany Erickson |
| Program | Geophysics, SPSE-Study of Physics of Earth |
| Start date | 05/01/2024 |
| Abstract | What it is about one fault that causes it to slip suddenly, unleashing catastrophic earthquakes, while another just creeps along steadily or produces smaller, more frequent earthquakes? This is difficult to assess because faults cannot be directly observed at depths where earthquakes start, typically 5 to 15 miles below ground. We must rely instead on indirect measurements made by instruments at the Earth's surface, and computer models representing the fault and how it slips in response to press |
| Source | NSF Awards |
$799/mo
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