Aerodynamic analysis of different cyclist hill descent positions

Blocken, Bje Bert; Druenen, Thijs van; Toparlar, Yasin; Andrianne, Thomas

doi:10.1016/j.jweia.2018.08.010

Cited by 57 publications

(39 citation statements)

References 32 publications

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“…Among the different strategies to improve the winning time and increase the efficient (thus, minimize the energy cost) cyclists use vary the body positions. It is possible to identify three main positions: (1) the upright position; (2) handlebar drops (dropped position) (3) leaning on the elbows (elbows position) (Defraeye et al, 2010a;Blocken et al, 2018). The numerical simulations seem to be one of the most precise methods to assess aerodynamics (Forte et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures

Forte¹,

Marinho

Barbosa

et al. 2020

Front. Bioeng. Biotechnol.

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The aim of this study was to use numerical simulations and analytical procedures to compare a cyclist's performance in three different cycling positions. An elite level road cyclist competing at a national level was recruited for this research. The bicycle was 7 kg and the cyclist 55 kg. A 3D scan was taken of the subject on the competition bicycle, wearing race gear and helmet in the upright position, in the handlebar drops (dropped position) and leaning on the elbows (elbows position). Numerical simulations by computer fluid dynamics in Fluent CFD code assessed the coefficient of drag at 11.11 m/s. Following that, a set of assumptions were employed to assess cycling performance from 1 to 22 m/s. Drag values ranged between 0.16 and 99.51 N across the different speeds and positions. The cyclist mechanical power in the elbows position differed from the upright position between 0 and 23% and from the dropped position from 0 to 21%. The cyclist's energy cost in the upright position differed 2 to 16% in comparison to the elbows position and the elbows position had less 2 to 14% energy cost in comparison to the dropped position. The estimated time of arrival was computed for a 220,000 m distance and it varied between 7,715.03 s (2 h:8 min:24 s) and 220,000 s (61 h:6 min:40 s) across the different speeds and positions. In the elbows position, is expected that a cyclist may improve the winning time up to 23% in comparison to he upright and dropped position across the studied speeds.

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Section: Introductionmentioning

confidence: 99%

Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures

Forte¹,

Marinho

Barbosa

et al. 2020

Front. Bioeng. Biotechnol.

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“…The drag experienced by a cyclist is associated with a complicated aerodynamic flow around a threedimensional contoured body, for which the phenomenon of flow separation plays a significant role. As noted in the literature (Lukes et al 2005;Defraeye et al 2010aDefraeye et al , b, 2011Blocken et al 2018), the aerodyamic flow is strongly dependent upon the posture of a cyclist. Defraeye et al (2010a) conducted a numerical and experimental study for a cyclist at the upright, dropped and time trial positions, respectively.…”

Section: Introductionmentioning

confidence: 86%

On the aerodynamic flow around a cyclist model at the hoods position

Miau

Tsai

et al. 2019

J Vis

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Aerodynamic flow around an 1/5 scale cyclist model was studied experimentally and numerically. First, measurements of drag force were performed for the model in a low-speed wind tunnel at Reynolds numbers from 5:5 Â 10 4 to 1:8 Â 10 5. Meanwhile, numerical computation using a large eddy simulation method was performed at three Reynolds numbers of 1:1 Â 10 4 , 6:5 Â 10 4 and 1:5 Â 10 5 to obtain the drag coefficients for comparison. Second, flow visualization was made in a water channel and the wind tunnel mentioned to examine the three-dimensional flow separation pattern on the model surface, which could also be realized from the numerical results. Finally, a wake flow survey based on the hot-wire measurements in the wind tunnel showed that in the near-wake region, the flow was featured with the formation of multiple streamwise vortices. The numerical results further indicated that these vortices were evolved from the separated flows occurred on the model surface.

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“…Figure 3 indicates that the mesh resolution in the wake is fairly coarse. Even though this resolution resulted from grid sensitivity studies in the previous publications that included several different cyclist positions [9,42,43], further research is needed to determine how near-wake grid resolution affects the computed drag and surface pressure distributions for sprint positions.…”

Section: Limitations and Further Workmentioning

confidence: 99%

CFD analysis of an exceptional cyclist sprint position

et al. 2019

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A few riders have adopted a rather exceptional and more aerodynamic sprint position where the torso is held low and nearly horizontal and close to the handle bar to reduce the frontal area. The question arises how much aerodynamic benefit can be gained by such a position. This paper presents an aerodynamic analysis of both the regular and the low sprint position in comparison to three more common cycling positions. Computational fluid dynamics simulations are performed with the 3D RANS simulations and the transition SST k-ω model, validated with wind-tunnel measurements. The results are analyzed in terms of frontal area, drag coefficient, drag area, air speed and static pressure distribution, and static pressure coefficient and skin friction coefficient on the cyclist surfaces. It is shown that the drag area for the low sprint position is 24% lower than for the regular position, which renders the former 15% faster than the latter. This 24% improvement is not only the result of the 19% reduction in frontal area, but also caused by a reduction of 7% in drag coefficient due to the changed body position and the related changes in pressure distribution. Evidently, specific training is required to exert large power in the low sprint position.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Aerodynamic analysis of different cyclist hill descent positions

Cited by 57 publications

References 32 publications

Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures

Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures

On the aerodynamic flow around a cyclist model at the hoods position

CFD analysis of an exceptional cyclist sprint position

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