Authors:
Kazuya Seo
and
Kana Takaoka
Affiliation:
Yamagata University, Japan
Keyword(s):
Sports Engineering, Discus, Equipment, Skills in Sports, Robustness, Flight Distance.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Multiobjective Optimization
;
Soft Computing
Abstract:
This paper describes the concurrent optimization of flight distance and ‘robustness’ of the equipment and skills in a discus. Two objective functions are considered. One is the flight distance, and the other is robustness. Robustness is defined as insensitivity to deviations from the local optimal release conditions. The aim of the optimization is to maximize both the flight distance and the robustness. Fourteen design variables are considered. Eight of the fourteen are concerned with the skill of the thrower. They determine the launch conditions, which are controlled by the thrower when he or she throws. The other six variables are concerned with the design of the equipment. These are the dimensions of the discus, the moment of inertia about the transverse axis and finally the mass of the discus. The dependences of size and the angle of attack on the aerodynamic data are estimated by using CFD (computational fluid dynamics) technique. It was found that there is a trade-off between f
light distance and robustness. The flight distance is 78.8 meters at the sweet spot solution, where both objective functions have better values simultaneously. The stalling angle for the sweet spot solution is relatively high.
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