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Title: Simulation of transition and roughness effects on micro air vehicle aerodynamics
Author: Liu, Sheng
ISNI:       0000 0004 5350 5109
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2014
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Accurate simulations on smooth and rough surfaces are of practical importance for micro air vehicle (MAV) design. This work includes the investigations of the models’ capability used in the aerodynamic simulation, and the numerical investigations of roughness effects on low Reynolds number aerodynamics for rough aerofoils and an MAV platform. Firstly, the low Re SST, γ-Reθ SST and low Re DDES-SST models are compared with an experiment on the smooth NACA 2415 aerofoil at Re = 1×105. It is found that both low Re SST and γ-Reθ SST models have a reasonably good capability to predict lift, drag and bubble between 4º ≤ α ≤ 8º. The low Re DDES-SST model performs better at α = 12º than 4º, predicting the best matched lift and resolving more transitional flow features. Secondly, the low Re SST and γ-Reθ SST models incorporated with the equivalent sand grain roughness method are compared with an experiment on a rough NACA 0012 aerofoil at Re = 1.5×105. The roughness result shows, while the low Re SST model predicts the correct trend of the roughness effects, the γ-Reθ SST model fails to predict the transition on the rough aerofoil surface, resulting in inaccurate lift and drag prediction. Thirdly, the investigations on rough aerofoils between Re = 2×104 ~ 2×105 shows the beneficial roughness effects only occur under an appropriate combination of Reynolds number, roughness height, incidence and aerofoil. A detailed guidance and suggestions of the application of roughness are proposed. The study also enriches the understanding of roughness effects at very low Reynolds numbers. Finally, the roughness investigation on the MAV platform shows better lift to drag ratios due to the rough thin wing are small at the lowest Reynolds number. A higher aspect ratio wing and better wing-fuselage integration may obtain more benefits from roughness.
Supervisor: Qin, Ning Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available