Abstract
A cycling peloton is the main group of cyclists riding closely together to reduce aerodynamic drag and energy expenditure. Previous studies on small groups of in-line drafting cyclists showed reductions down to 70 to 50% the drag of an isolated rider at same speed and these values have also been used for pelotons. However, inside a tightly packed peloton with multiple rows of riders providing shelter, larger drag reductions can be expected. This paper systematically investigates the drag reductions in two pelotons of 121 cyclists. High-resolution CFD simulations are performed with the RANS equations and the Transition SST-k-ω model. The cyclist wall-adjacent cell size is 20 μm and the total cell count per peloton is nearly 3 billion. The simulations are validated by four wind-tunnel tests, including one with a peloton of 121 models. The results show that the drag of all cyclists in the peloton decreases compared to that of an isolated rider. In the mid rear of the peloton it reduces down to 5%–10% that of an isolated rider. This corresponds to an “equivalent cycling speed” that is 4.5 to 3.2 times less than the peloton speed. These results can be used to improve cycling strategies.
Original language | English |
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Pages (from-to) | 319-337 |
Number of pages | 19 |
Journal | Journal of Wind Engineering and Industrial Aerodynamics |
Volume | 179 |
DOIs | |
Publication status | Published - 1 Aug 2018 |
Funding
The work in this paper has been made possible by supercomputing with ANSYS Fluent CFD software on Cray supercomputers. The authors gratefully acknowledge the collaboration with ANSYS (Wim Slagter, Rongguang Jia, Shriram Jagannathan) and CRAY (Jef Dawson, David Whitaker) for running the peloton simulation jobs. This work was also sponsored by NWO Exacte en Natuurwetenschappen (Physical Sciences) for the use of supercomputer facilities, with financial support from the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research, NWO) for the subconfiguration validation studies. The authors are very grateful to Custom Company (Jaspal Bathal), FlexForm (Frank Broos) and Tenax (Ronnie van Grunsven) for the efficient casting of the 121 high-quality cyclist models for the wind tunnel tests conducted at Eindhoven University of Technology. The authors thank ANSYS for contributing to the model casting costs. The authors are also very grateful to the anonymous reviewers for their very valuable and constructive comments on this paper.
Keywords
- Aerodynamic resistance
- Computational fluid dynamics
- Cycling aerodynamics
- Sports
- Wind tunnel testing
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