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Success in track cycling requires high athlete power and low aerodynamic losses. The latter is primarily dominated by rider position, and athletes and trainers will spend countless hours seeking any slight reduction. This is largely accomplished via trial and error either on the track or in an expensive wind tunnel. This project aims to help Canadian Olympic athletes improve their aerodynamic positioning using computational fluid mechanics. A rider is scanned into a computer model, which can then be rigorously tested in a variety of configurations. In this study, drag predicted through simulation will be validated against track data, after which the computational framework will be used for optimal bike component selection to help Canadian athletes Own the Podium.
Engineering - mechanical
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