The National Science Foundation awarded a $574,200 Project Grant to the University of California Irvine under the Engineering federal grant program (CFDA 47.041) from April 2023 through March 2028. Through this award, UC Irvine will develop a framework to optimize material composition design under uncertainty at small length scales, quantifying effects on component properties. The university will convert the design problem into a statistical learning problem leveraging machine learning to enable informed decision-making regarding resource allocation, uncertainty quantification, and anomaly detection. UC Irvine will demonstrate the framework's impact optimizing complex alloy design with applications in energy storage, cryogenic conditions. Educational materials, summer workshops, and a design optimization app will be produced to benefit students and local businesses. If successful, the proposed methodological contributions could broadly aid multidisciplinary systems analysis applications.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $574.2k | 4/19/23 |