Identifying race time benefits of best practice in freestyle swimming using simulation

Abstract

In the preparation of a swimmer for a race, it is not currently possible to determine the race time impacts of changes to equipment or technique. This study addresses this problem, by modelling the resistive and propulsive forces experienced by a swimmer, throughout the various phases of a race, to predict race time.
Swimming resistance is quantified for surface and underwater swimming, across a population of swimmers, using computational methods and bespoke measurement equipment. Due to the low repeatability, when measuring swimming resistance, statistical methods are utilised to quantify confidence in the measured data. For five repeat tests a 1.8% difference in swimming resistance can be resolved with 95% confidence. Arm propulsion is modelled, treating the arm as a single element moving through the water, producing drag. Leg propulsion is modelled using Large Amplitude Elongated Body Theory originally derived by Lighthill to predict the propulsion generated by fish. This enables freestyle flutter kick, when swimming on the surface, and underwater undulatory swimming, after the start and turn, to be modelled. Input motion for both arm and leg propulsion is determined from manual digitisation of video data, providing the body kinematics of a kick and the time accurate arm speed. Accurate swimming speed for a given stroke rate is achieved by comparing the simulated output with experimental data and scaling the arm and leg parameters. Using a race phase algorithm, the swimming speed for each phase of a swimming race is simulated.
To simulate fatigue, metabolic energy sources are considered. Both maximum power and energy capacity, for aerobic and anaerobic energy sources, are determined from literature. Using PI control of stroke rate, swimming fatigue is simulated by ensuring the propulsive power does not exceed the total available power from the energy model. Therefore, as a swimmer progresses through a race, the available power depletes, causing stroke rate and hence swimming speed to decay.
Combining these models, enables simulation of swimming speed and fatigue throughout a race, from which race time is predicted. The race time impact of changes to swimming resistance and propulsion are investigated. Resistance and propulsion changes from equipment, drafting and technique are quantified experimentally. A 9.5% reduction in swimming resistance, affecting the whole race or underwater phases only, has been found to improve a 100 m race time by 2.75s or 0.99s respectively.

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ORCID for S.R. Turnock: orcid.org/0000-0001-6288-0400

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