This National Science Foundation (NSF) Project Grant award under the Engineering program (CFDA 47.041) for $259,701 aims to develop a novel hierarchical adjoint-based data assimilation framework to improve the accuracy and efficiency of turbulence flow modeling and prediction. The key products/services to be delivered include: Development of open-source software tools encapsulating the hierarchical adjoint-based data assimilation (HADA) framework, which will be made available to researchers and practitioners to promote broader usage and further development. The project will provide documentation and tutorials to facilitate ease of use. Technical advancement of adjoint-based data assimilation techniques by employing an optimal eddy viscosity model to stabilize the adjoint fields and enhance performance in turbulent flows. The hierarchical methodology will gradually reconstruct flow fields across a hierarchy of spatial and temporal resolutions to reduce computational demands. Delivery of a reliable, efficient, and scalable state estimation tool that can advance inverse problems for engineering and environmental systems, with potential applications in areas such as weather forecasting, climate modeling, and pollution dispersion. The award is held by the San Diego State University Research Foundation, a non-profit organization that provides research, analytical, and technical services to federal agencies. The project period runs from August 15, 2023 to July 31, 2026.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $259.7k | 9/13/23 |