Design Optimization of Subcavitating Hydrofoils for America's Cup Class Yachts

The optimization process we employ is grade-based, allowing for efficient gradient computation. We utilize SNOs, and it's a privilege to have President Michael Saunders, who significantly contributes to SNO development, in the audience today.

To modify the geometry of the foil or a 3D shape, we require a geometry parameterization. Following this, it is essential to adapt the mesh automatically based on the gradients. The Computational Fluid Dynamics (CFD) solver we use is based on the Reynolds-Averaged Navier-Stokes (RANS) equations. While this approach offers low fidelity, it serves its purpose in our framework. A critical component of this process is the adjoint solver, which is a vital part of Professor Jimmy's legacy that I have built upon.

As an illustrative example, we can start with a basic shape, such as a circle or cylinder, which typically generates high drag and minimal lift. Our optimization process then seeks to minimize drag for a specified lift in transonic flow conditions. The optimization identifies necessary modifications, such as flattening the shape to reduce pressure drag, rounding the leading edge, and sharpening the trailing edge, ultimately leading to the creation of a supercritical airfoil design.

Additionally, we can extend our optimization to 3D shapes. A notable example is the "crappy wing," which is a random variation of a shape. Our optimization successfully achieves a smooth pressure distribution for this design, demonstrating the effectiveness of our approach over time.