Aerodynamic shape optimization has the potential to fully automate the aerodynamic design process. The optimizer relies heavily on a robust, accurate, and efficient computational fluid dynamics (CFD) solver. High-order CFD methods have the potential to provide high-accurate solutions but rely on adaptation for robustness and efficiency to strategically distribute degrees of freedom to minimize error for a given cost.

This dissertation closes many gaps preventing the widespread adoption of high-order methods in shape optimization. A novel curved mesh adaptation method is developed that performs metric-based adaptation on curved meshes improving robustness. An algorithm is developed to adapt the mesh during optimization that balances optimization cost and adaptation cost while ensuring accuracy at the optimum. These methods enable cost effective and accurate optimization.

Date/Location:
March 20th, 2025 | 10:00 am EDT | FXB 1044
https://umich.zoom.us/j/95480752465 | passcode: adapt