The performance of a bobsleigh depends significantly on the aerodynamic drag. In the aerodynamic development process there are routine tasks whose automation results in a considerable increase in development efficiency. In addition the application of an appropriate optimization algorithm can enhance the diversity of development trends. In this paper the fully automated optimization of the front and of the rear bumpers of a bobsleigh is shown. Deterministic and stochasitc optimization algorithms are applied and their suitability for constrained aerodynamic optimization problems are discussed. It becomes apparent that the deterministic algorithm converges faster when applied to a bound constrained optimization task while the stochastic algorithm performs better in case of a non-linearly constrained optimization task. Either way, after having set up the optimization task properly the fully automated shape development leads to a drag reduction of the bobsleigh components without further user interaction.
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