New Grant: Award Supports Cyberinfrastructure for Scalable Modeling of Solids and Fluids

Ramin Bostanabad and Aparna Chandramowlishwaran

 June 21, 2022 – Principal investigators: Ramin Bostanabad, assistant professor of mechanical and aerospace engineering, and co-principal investigator Aparna Chandramowlishwaran, associate professor of electrical engineering and computer science

Award: $600,000 over three years

Funding agency: National Science Foundation Office of Advanced Cyberinfrastructure

Project: Geometry-aware and Deep Learning-based Cyberinfrastructure for Scalable Modeling of Solids and Fluids

Many phenomena in solid and fluid mechanics are modeled via complex partial differential equations (PDEs). Since solving these PDEs via traditional numerical methods is prohibitively expensive, emulators such as deep neural networks (DNNs) are increasingly employed to approximate PDE solutions. While significant effort has been expended in this direction, existing technologies provide expensive solutions that are not transferable across different applications or scalable to complex PDEs. This project aims to address these limitations using a divide and conquer approach.

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