Aerodynamic benefits by optimizing cycling posture
Please always quote using this URN: urn:nbn:de:bvb:20-opus-285942
- An approach to aerodynamically optimizing cycling posture and reducing drag in an Ironman (IM) event was elaborated. Therefore, four commonly used positions in cycling were investigated and simulated for a flow velocity of 10 m/s and yaw angles of 0–20° using OpenFoam-based Nabla Flow CFD simulation software software. A cyclist was scanned using an IPhone 12, and a special-purpose meshing software BLENDER was used. Significant differences were observed by changing and optimizing the cyclist’s posture. Aerodynamic drag coefficient (CdA) variesAn approach to aerodynamically optimizing cycling posture and reducing drag in an Ironman (IM) event was elaborated. Therefore, four commonly used positions in cycling were investigated and simulated for a flow velocity of 10 m/s and yaw angles of 0–20° using OpenFoam-based Nabla Flow CFD simulation software software. A cyclist was scanned using an IPhone 12, and a special-purpose meshing software BLENDER was used. Significant differences were observed by changing and optimizing the cyclist’s posture. Aerodynamic drag coefficient (CdA) varies by more than a factor of 2, ranging from 0.214 to 0.450. Within a position, the CdA tends to increase slightly at yaw angles of 5–10° and decrease at higher yaw angles compared to a straight head wind, except for the time trial (TT) position. The results were applied to the IM Hawaii bike course (180 km), estimating a constant power output of 300 W. Including the wind distributions, two different bike split models for performance prediction were applied. Significant time saving of roughly 1 h was found. Finally, a machine learning approach to deduce 3D triangulation for specific body shapes from 2D pictures was tested.…
Author: | Alois Schaffarczyk, Silas Koehn, Luca Oggiano, Kai Schaffarczyk |
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URN: | urn:nbn:de:bvb:20-opus-285942 |
Document Type: | Journal article |
Faculties: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Language: | English |
Parent Title (English): | Applied Sciences |
ISSN: | 2076-3417 |
Year of Completion: | 2022 |
Volume: | 12 |
Issue: | 17 |
Article Number: | 8475 |
Source: | Applied Sciences (2022) 12:17, 8475. https://doi.org/10.3390/app12178475 |
DOI: | https://doi.org/10.3390/app12178475 |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten |
7 Künste und Unterhaltung / 79 Sport, Spiele, Unterhaltung / 790 Freizeitgestaltung, darstellende Künste, Sport | |
Tag: | aerodynamic drag reduction; cycling; drag area; machine learning |
Release Date: | 2023/09/06 |
Date of first Publication: | 2022/08/25 |
Licence (German): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |