If you have ever seen the front wing of a Formula 1 vehicle, you would think you are staring at a piece of modern art and not one of the greatest contributors to the downforce and handling of the vehicle. Current front wing designs are intricate and no two are the same, a testament to the complexity of the flowfield experienced by each vehicle as it makes its way around the track. Simplifying the design and looking at just the twist distribution, there is still little to no agreement found. Hence the purpose of this study. Can we identify the optimal twist distribution for the front wing of a race car that maximizes downforce without increasing drag? It turns out that we can.
By using ModelCenter from Phoenix Integration as an integration platform, Pointwise to generate the meshes, and AcuSolve to run the CFD calculations, push-button design optimization was achieved. In fact, the model-centric process was built on parametric geometry so that a single mesh could be mapped effortlessly from one design iteration to the next and the final output is an actual CAD model that can be used for further analysis.
- Formulating the optimization problem including the model and design variables and setting up the integration platform
- Generating a baseline mesh that isolates the area of interest and automating the parametric mapping for each design iteration
- Locating the optimum twist distribution for maximum downforce using a genetic algorithm on a response surface