This paper proposes a methodology to explore the optimal design space of sports equipment, where non-linear dynamics play a key role, with the goal of gaining creative insights. In the presented example, this space encompasses both the optimal launch conditions and the optimal sizes of a discus to maximize flight distance. The optimization procedure is divided into four steps. The first step calculates the aerodynamic forces acting on a discus using computational fluid dynamics. The second step optimizes the discus flight distance for launch conditions. This step provides the maximum attainable flight distance and the optimal launch conditions for each candidate discus design, that is, the optimal skill of the athlete. The third step is Bayesian optimization of the flight distance. Bayesian optimization identifies the promising design set of design variables, that is, equipment (discus). Finally, the fourth step explores the optimal space using self-organizing maps, providing creative insights for an optimal aerodynamic design space. It was found that discus thickness is the most crucial design variable, with the thinner discus achieving longer flight distances due to the greater maximum lift coefficient. Regarding launch conditions, the initial flight path angle is the most important parameter, ideally about 40 degrees with a narrow tolerance window.
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