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The aim of this study was to analyze the effects of depth on drag during the streamlined glide in swimming using Computational Fluid Dynamics. The Computation Fluid Dynamic analysis consisted of using a three-dimensional mesh of cells that simulates the flow around the considered domain. We used the K-epsilon turbulent model implemented in the commercial code Fluent® and applied it to the flow around a three-dimensional model of an Olympic swimmer. The swimmer was modeled as if he were gliding underwater in a streamlined prone position, with hands overlapping, head between the extended arms, feet together and plantar flexed. Steady-state computational fluid dynamics analyses were performed using the Fluent® code and the drag coefficient and the drag force was calculated for velocities ranging from 1.5 to 2.5 m/s, in increments of 0.50m/s, which represents the velocity range used by club to elite level swimmers during the push-off and glide following a turn. The swimmer model middle line was placed at different water depths between 0 and 1.0 m underwater, in 0.25m increments. Hydrodynamic drag decreased with depth, although after 0.75m values remained almost constant. Water depth seems to have a positive effect on reducing hydrodynamic drag during the gliding. Although increasing depth position could contribute to decrease hydrodynamic drag, this reduction seems to be lower with depth, especially after 0.75 m depth, thus suggesting that possibly performing the underwater gliding more than 0.75 m depth could not be to the benefit of the swimmer.
EN
In this paper, the discrete differentiation order functions of the variable, fractional-order PD controller (VFOPD) are considered. In the proposed VFOPD controller, a variable, fractional-order backward difference is applied to perform closed-loop, system error, discrete-time differentiation. The controller orders functions which may be related to the controller input or output signal or an input and output signal. An example of the VFOPD controller is applied to the robot arm closed-loop control due to system changes in moment of inertia. The close-loop system step responses are presented.
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