LEAPS-MPS: Strong convergence of numerical methods for solving nonlinear stochastic PDEs — NSF Award to The University of Texas Ri
Many natural and engineered systems from weather patterns and ocean currents to biological processes, are governed by dynamics that are inherently uncertain or randomly influenced. Understanding these systems requires accurate simulation of complex equations that combine deterministic laws with random effects. Stochast
| Award title | LEAPS-MPS: Strong convergence of numerical methods for solving nonlinear stochastic PDEs |
|---|---|
| Award ID | 2530211 |
| Awardee | The University of Texas Rio Grande Valley |
| City | EDINBURG |
| State | TX |
| Amount obligated | $249,956 |
| Principal investigator | Liet Vo |
| Program | OFFICE OF MULTIDISCIPLINARY AC |
| Start date | 09/01/2025 |
| Abstract | Many natural and engineered systems from weather patterns and ocean currents to biological processes, are governed by dynamics that are inherently uncertain or randomly influenced. Understanding these systems requires accurate simulation of complex equations that combine deterministic laws with random effects. Stochastic partial differential equations (SPDEs) provide the mathematical foundation for modeling such systems under uncertainty. One particularly important example is the stochastic Navi |
| Source | NSF Awards |
$799/mo
Try NSFGrants →