Aerodynamic optimization of athlete posture using virtual skeleton methodology and computational fluid dynamics

Abstract

An athlete’s posture has a significant impact on aerodynamic drag. Although aerodynamic drag in different sports has been studied extensively, most studies have analysed only a limited number of positions, and no generalized methods for optimization are available. In this work, we present a methodology to perform athlete posture optimization with respect to aerodynamic drag reduction. The method combines the virtual skeleton methodology to adjust the athlete’s posture, CFD simulations to evaluate the drag for a given posture, and efficient global optimization to find the optimum position. We demonstrate the method by optimizing the time trial position for a cyclist. The cyclist position was parameterized with 6 design parameters, and the optimization required 41 CFD simulations to converge. The optimal posture yielded a reduction in drag of 17 % compared to the initial posture (disregarding bicycle drag). The method has potential to make posture optimization more accessible across a wide range of sports, and lead to insight into the aerodynamic influence of posture in general.