This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $361,985 to the University of Wisconsin System to develop predictive mathematical models for manufacturing processes involving complex polymeric materials. The project aims to leverage recent advances in experimental methods and data science to better understand the relationship between the flow and microstructure of these materials, which is critical for applications like printed electronics, photonics, and solar cells. The research team will create large, rich datasets on the time-evolution of flow and microstructure in complex fluid flows, and then integrate machine learning, data assimilation, and physics-informed modeling to develop predictive models for fluid structure and stress in materials where no first-principles models currently exist. The project represents a collaborative effort to drive transformational progress in data-driven modeling of flowing complex fluids. The award period runs from April 1, 2024 to March 31, 2027.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $362.0k | 4/9/24 |