Control of flow around a low Reynolds number airfoil using longitudinal strips

2018 ◽  
Vol 3 (11) ◽  
Author(s):  
Seunghyun Cho ◽  
Jooha Kim ◽  
Haecheon Choi
Keyword(s):  
Reynolds Number ◽  
Low Reynolds Number ◽  
Control Of Flow ◽  
Low Reynolds ◽  
Low Reynolds Number Airfoil

Experimental Comparison of DBD Plasma Actuators for Low Reynolds Number Separation Control

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Christopher R. Marks ◽  
Rolf Sondergaard ◽  
Mitch Wolff ◽  
Rich Anthony
Keyword(s):  
Reynolds Number ◽  
Low Reynolds Number ◽  
Turbine Blades ◽  
Plasma Actuators ◽  
Experimental Comparison ◽  
Separation Control ◽  
Suction Surface ◽  
Dbd Plasma ◽  
Low Reynolds ◽  
Low Reynolds Number Airfoil

This paper presents experimental work comparing several Dielectric Barrier Discharge (DBD) plasma actuator configurations for low Reynolds number separation control. Actuators studied here are being investigated for use in a closed loop separation control system. The plasma actuators were fabricated in the U.S. Air Force Research Laboratory Propulsion Directorate’s thin film laboratory and applied to a low Reynolds number airfoil that exhibits similar suction surface behavior to those observed on Low Pressure (LP) Turbine blades. In addition to typical asymmetric arrangements producing downstream jets, one electrode configurations was designed to produce an array of off axis jets, and one produced a spanwise array of linear vertical jets in order to generate vorticity and improved boundary layer to freestream mixing. The actuators were installed on an airfoil and their performance compared by flow visualization, surface stress sensitive film (S3F), and drag measurements. The experimental data provides a clear picture of the potential utility of each design. Experiments were carried out at four Reynolds numbers, 1.4 × 105, 1.0 × 105, 6.0 × 104, and 5.0 × 104 at a-1.5 deg angle of attack. Data was taken at the AFRL Propulsion Directorate’s Low Speed Wind Tunnel (LSWT) facility.

Experimental and Numerical Investigation of Transition Effects on a Low Reynolds Number Airfoil

2017 ◽  
Author(s):  
Michael J. Collison ◽  
Peter X. L. Harley ◽  
Domenico di Cugno
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Separation Bubble ◽  
Low Reynolds Number ◽  
Flow Visualisation ◽  
Transition Model ◽  
Laminar Separation ◽  
Oil Flow ◽  
Low Reynolds ◽  
Low Reynolds Number Airfoil

Low speed, small scale turbomachinery operates at low Reynolds number with transition phenomena occurring. In small consumer product applications, high efficiency and low noise are key performance metrics. Transition behaviour will partly determine the state of the boundary layer at the trailing edge; whether it is laminar, turbulent or separated impacts aerodynamic and acoustic performance. This study aimed to evaluate a commercially available CFD transition model on a low Reynolds number Eppler E387 airfoil and identify whether it was able to correctly model the boundary layer transition, and at what expense. CFD was carried out utilising the ANSYS Shear Stress Transport (SST) k-ω γ-Reθ transition model. The CFD progressed from 2D in Fluent v150, through to single cell thickness 3D (pseudo 2D) in CFX v172. An Eppler E387 low Reynolds number airfoil, for which experimental data was readily available from literature at Re = 200,000 was used as the validation case for the CFD, with results computed at numerous incidence angles and mesh densities. Additionally, experimental surface oil flow visualisation was undertaken in a wind tunnel using a scaled E387 airfoil for the zero incidence case at Re = 50,000. The flow visualisation exhibited the expected key features of transition in the breakdown of the boundary layer from laminar to turbulent, and was used as a validation case for the CFD transition model. The comparison between the results from the CFD transition model and the experimental data from literature suggested varying levels of agreement based on the mesh density and CFD solver in the starting location of the laminar separation bubble, with higher disparity for the position of the reattachment point. Whether 2D or 3D, the prediction accuracy was seen to worsen at high incidence angles. Finally, the location of the laminar separation bubble between CFD and oil flow visualisation had good agreement and a set of guidelines on the mesh parameters which can be applied to low Reynolds number turbomachinery simulations was determined.

Low-Reynolds-number airfoil design optimization using deep-learning-based tailored airfoil modes

2021 ◽  
pp. 107309
Author(s):  
Jichao Li ◽  
Mengqi Zhang ◽  
Chien Ming Jonathan Tay ◽  
Ningyu Liu ◽  
Yongdong Cui ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Deep Learning ◽  
Design Optimization ◽  
Low Reynolds Number ◽  
Low Reynolds ◽  
Low Reynolds Number Airfoil

Experimental Dynamic Stall study on a low Reynolds number airfoil

2015 ◽  
Author(s):  
Santiago Algozino ◽  
Julio Marañon Di Leo ◽  
Juan Delnero ◽  
Guillermo Capittini
Keyword(s):  
Reynolds Number ◽  
Low Reynolds Number ◽  
Dynamic Stall ◽  
Low Reynolds ◽  
Low Reynolds Number Airfoil
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