Aerodynamic Optimization of a Reduced Scale Model of a Ground Vehicle with a Shape Morphing Technique

Aerodynamic performances of ground vehicle continuously improve and a lot both wind tunnel measurements Computational Fluid Dynamics (CFD) investigations contribute in the identification local zones where shape deformation can lead to drag force reduction. Gradient-based optimization with optimal system involving CFD models is one powerful methods for optimization, but genetic algorithm applied on surrogate model also explore large design space reasonable period computation time. In this paper, we present an aerodynamic technique using Kriging order perform simulations different front air dam geometries situated below bumper reduced scale road vehicle. A first design-of-experiment (DoE) undertaken Large Eddy Simulations (LES), height geometric parameters radial-basis-function dam, utilizing Sobol algorithm. Then, multi-objective-genetic-algorithm (MOGA) constituted model, depending reach minimum coefficient value by considering pressure constraints. Results show that increase at rear tailgate, especially slowing airflow underfloor, optimum balance necessary not stagnation leading loss benefit. The driven enables retrieval airdam shapes found tests, even relatively coarse numerical meshes used simulations.