Low Reynolds number effects on aerodynamic loads of a small scale wind turbine

2020 ◽  
Vol 154 ◽  
pp. 1283-1293 ◽  
Author(s):  
Hakjin Lee ◽  
Duck-Joo Lee
Keyword(s):  
Reynolds Number ◽  
Wind Turbine ◽  
Low Reynolds Number ◽  
Small Scale ◽  
Aerodynamic Loads ◽  
Reynolds Number Effects ◽  
Low Reynolds

Design Considerations, Performance Enhancing Techniques, and Wind Tunnel Testing for Small-Scale, Low Reynolds Number Wind Turbines

2011 ◽  
Author(s):  
Jason R. Gregg ◽  
Timothy A. Burdett ◽  
Kenneth W. Van Treuren ◽  
Stephen T. McClain
Keyword(s):  
Reynolds Number ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Low Reynolds Number ◽  
Small Scale ◽  
Wind Tunnel Testing ◽  
Low Reynolds ◽  
Lift And Drag

Wind turbines have become a significant part of the world’s energy equation and are expected to become even more important in the years to come. A much-neglected area within wind turbine research is small-scale, fixed-pitch wind turbines with typical power outputs in the 1–10 kW range. This size wind system would be ideal for residential and small commercial applications. The adoption of these systems could reduce dependence on the aging U.S. power grid. It is possible to optimize a small-scale system to operate more efficiently at lower wind speeds, which will make wind generation possible in areas where current wind technology is not feasible. This investigation examines the use of the S818 airfoil, a typical blade root airfoil designed by the National Renewable Energy Laboratory (NREL), as a basis for the design of low Reynolds number (less than 200,000) systems. The literature shows that many of the airfoils proposed for wind turbine applications, including the S818, only have lift and drag data generated by numerical simulations. In previous research at Baylor, 2-D simulations published by NREL have been shown to predict an optimal design angle of attack (which is the angle at which L/D is maximized) up to 2.25° different from actual wind tunnel data. In this study, the lift and drag generated by the S818 airfoil has been measured experimentally at a Reynolds number of approximately 150,000 and compared with NREL simulation data, showing a discrepancy of 1.0°. Using the S818 airfoil, a set of wind turbine blades has been designed to collect wind turbine power data in wind tunnel testing. Design parameters investigated include the effect of design tip speed ratios (TSR) (1, 3, and 7) and the influence of the number of blades (2, 3 and 4) on power generated. At the low Reynolds numbers tested (ranging from 14,000–43,200 along the blade for a design TSR of 3 and a wind speed of 10 mph), the effect of roughness was explored as a performance enhancing technique and was seen to increase power output by delaying separation. Under these low Reynolds number conditions, separation typically occurs on smooth blades. However, the roughness acted as a passive flow control, keeping the flow attached and increasing power output. Preliminary data suggest that as much as a 50% improvement can be realized with the addition of roughness elements for a TSR of 3. Additionally, the increase in power output due to roughness is comparable with the increase in power due to adding another smooth blade.

Adjoint-Based Aerodynamic Shape Optimization for Low Reynolds Number Airfoils

2015 ◽  
Vol 138 (2) ◽  
Author(s):  
Juanmian Lei ◽  
Jiandong He
Keyword(s):  
Reynolds Number ◽  
Shape Optimization ◽  
Low Reynolds Number ◽  
Boundary Layer Separation ◽  
Small Scale ◽  
Test Case ◽  
Aerodynamic Shape Optimization ◽  
Aerodynamic Shape ◽  
Aerial Vehicles ◽  
Low Reynolds

In the past decades, most of the research studies on airfoil shape design and optimization were focused on high Reynolds number airfoils. However, low Reynolds number airfoils have attracted significant attention nowadays due to their vast applications, ranging from micro-aerial vehicles (MAVs) to small-scale unmanned aerial vehicles. For low Reynolds number airfoils, the unsteady effects caused by boundary layer separation cannot be neglected. In this paper, we present an aerodynamic shape optimization framework for low Reynolds number airfoil that we developed based on the unsteady laminar N–S equation and the adjoint method. Finally, using the developed framework, we performed a test case with NACA0012 airfoil as a baseline configuration and the inverse of lift to drag ratio as the cost function. The optimization was carried out at Re = 10,000 and Ma = 0.2. The results demonstrate the effectiveness of the framework.

A bioinspired Separated Flow wing provides turbulence resilience and aerodynamic efficiency for miniature drones

2020 ◽  
Vol 5 (38) ◽  
pp. eaay8533 ◽  
Author(s):  
Matteo Di Luca ◽  
Stefano Mintchev ◽  
Yunxing Su ◽  
Eric Shaw ◽  
Kenneth Breuer
Keyword(s):  
Reynolds Number ◽  
Wind Tunnel ◽  
Low Reynolds Number ◽  
Substantial Reduction ◽  
Separated Flow ◽  
Small Scale ◽  
Freestream Turbulence ◽  
Flight Duration ◽  
Aerodynamic Efficiency ◽  
Low Reynolds

Small-scale drones have enough sensing and computing power to find use across a growing number of applications. However, flying in the low–Reynolds number regime remains challenging. High sensitivity to atmospheric turbulence compromises vehicle stability and control, and low aerodynamic efficiency limits flight duration. Conventional wing designs have thus far failed to address these two deficiencies simultaneously. Here, we draw inspiration from nature’s small flyers to design a wing with lift generation robust to gusts and freestream turbulence without sacrificing aerodynamic efficiency. This performance is achieved by forcing flow separation at the airfoil leading edge. Water and wind tunnel measurements are used to demonstrate the working principle and aerodynamic performance of the wing, showing a substantial reduction in the sensitivity of lift force production to freestream turbulence, as compared with the performance of an Eppler E423 low–Reynolds number wing. The minimum cruise power of a custom-built 104-gram fixed-wing drone equipped with the Separated Flow wing was measured in the wind tunnel indicating an upper limit for the flight time of 170 minutes, which is about four times higher than comparable existing fixed-wing drones. In addition, we present scaling guidelines and outline future design and manufacturing challenges.

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