Andreas Rauch

• Year

  2022

• Program

  AI in Sci

• Institution

  University of Michigan

• Field of Study

  Engineering

Developing the next generation of propulsion and power-generation devices requires an enhanced understanding of the multiphysics processes governing them. I am focused on developing data-driven physics-constrained models to provide high-fidelity computational tools for flow prediction and analysis.
Advances in both computational and experimental methods have generated significant high-resolution fluid dynamics data. However, the tools utilized for model development have not harnessed the potential of this data. Rather than using data to augment and drive model development, it is often only used for a-posteriori validation. I am interested in assimilating high-resolution data into computational models to increase simulation predictive capabilities and reduce computational cost.