Aerodynamic characteristics analysis of the tailback shape of a flying car based on LBM

Hongfei Liu; Jingyang Li; Hexi Baoyin

doi:10.1117/12.3026299

1 April 2024 Aerodynamic characteristics analysis of the tailback shape of a flying car based on LBM

Hongfei Liu, Jingyang Li, Hexi Baoyin

Proceedings Volume 13082, Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023); 1308220 (2024) https://doi.org/10.1117/12.3026299
Event: 2023 4th International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology (MEMAT 2023), 2023, Guilin, China

Abstract

The flying car combines the functions of the aircraft and the car, and its aerodynamic shape satisfies the aerodynamic characteristics of the car and the aircraft. The Catia three-dimensional modeling software is used to draw a ducted flying car shape, and the step-back, fast-back, and square-back type tailback models are established. The CFD software Xflow is used to perform grid-independent experiments on the model to determine the optimal simulation accuracy of the vehicle model. The aerodynamic analysis of the three tailback models is carried out by using the obtained optimal simulation accuracy. Through the analysis and comparison of the aerodynamic characteristics of the three tailback shapes, it is concluded that the aerodynamic parameters of the fast-back tailback are the best for improving aerodynamic performance. By comparing the inclination angle of the fast-back tailback, it is found that when the inclination angle is 30, the aerodynamic parameters improve the aerodynamic performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongfei Liu, Jingyang Li, and Hexi Baoyin "Aerodynamic characteristics analysis of the tailback shape of a flying car based on LBM", Proc. SPIE 13082, Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023), 1308220 (1 April 2024); https://doi.org/10.1117/12.3026299

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