Abstract
This paper describes the concurrent optimization of the design of a discus and the skill with which it is thrown. The objective function for optimization is the flight distance, where longer is better. Thirteen control variables are considered, twelve of which are concerned with the skill of the thrower. These determine the launch conditions, which are controlled by the thrower when he or she throws the discus. The final variable is concerned with the discus itself. This is the moment of inertia on its transverse axis. The optimization was carried out with the aid of a genetic algorithm, and the entire trend for each generation between the objective function and the control variables could be visualized with the aid of self organizing maps. It was found that the flight distance achieved with concurrent optimization was longer than that optimized for skill alone. In the case of the optimal flight, the angle of attack should always be less than the stalling angle.
Original language | English |
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Pages (from-to) | 170-175 |
Number of pages | 6 |
Journal | Procedia Engineering |
Volume | 34 |
DOIs | |
Publication status | Published - 2012 Jan 1 |
Event | 9th Conference of the International Sports Engineering Association, ISEA 2012 - Lowell, MA, United States Duration: 2012 Jul 9 → 2012 Jul 13 |
Keywords
- Concurrent optimization
- Data mining
- Discus
- Genetic algorithm
- Self-organizing map
ASJC Scopus subject areas
- Engineering(all)