29/09/2016 Engineering Physics
DOI: 10.1063/1.4963236 SemanticScholar ID: 125680675 MAG: 2524099857

Experimental study of surface curvature effects on aerodynamic performance of a low Reynolds number airfoil for use in small wind turbines

Publication Summary

This paper presents the wind tunnel experimental results to investigate the effects of surface gradient-of-curvature on aerodynamic performance of a low Reynolds number airfoil Eppler 387 for use in small-scale wind turbines. The prescribed surface curvature distribution blade design method is applied to the airfoil E387 to remove the gradient-of-curvature discontinuities and the redesigned airfoil is denoted as A7. Both airfoils are manufactured with high precision to reflect the design. Low-speed wind tunnel experiments are conducted to both airfoils at chord based Reynolds numbers 100 000, 200 000, and 300 000. Surface pressure measurements are used to calculate the lift and pitching-moment data, and the wake survey method is applied to obtain the drag data. The experimental results of E387 are compared with NASA Low Turbulence Pressure Tunnel (LTPT) results for validation. The gradient-of-curvature discontinuities of E387 result in a larger laminar separation bubble which causes higher drag at lower angles of attack. As the angle of attack increases the separation bubble of the airfoil E387 moves faster towards the leading edge than that of A7, resulting in a premature bubble bursting and earlier stall on E387. The impact of the gradient-of-curvature distribution on the airfoil performance is more profound at higher angles of attack and lower Reynolds number. The aerodynamic improvements are integrated over the 3D geometry of a 3 kW small wind turbine, resulting in up to 10% increase in instantaneous power and 1.6% increase in annual energy production. It is experimentally concluded that an improved curvature distribution results in a better airfoil performance, leading to higher energy output efficiency.

CAER Authors

Avatar Image for Eldad Avital

Dr. Eldad Avital

Queen Mary University of London - Reader in Computational (& Experimental) Fluids and Acoustics

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