Research Papers: Techniques and Procedures

Adjoint-Based Aerodynamic Shape Optimization for Low Reynolds Number Airfoils

[+] Author and Article Information
Juanmian Lei

School of Aerospace,
Beijing Institute of Technology,
Beijing 100081, China
e-mail: leijm@bit.edu.cn

Jiandong He

School of Aerospace,
Beijing Institute of Technology,
Beijing 100081, China
e-mail: chrishe1900@gmail.com

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received March 14, 2015; final manuscript received September 8, 2015; published online October 5, 2015. Assoc. Editor: Moran Wang.

J. Fluids Eng 138(2), 021401 (Oct 05, 2015) (6 pages) Paper No: FE-15-1171; doi: 10.1115/1.4031582 History: Received March 14, 2015; Revised September 08, 2015

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.

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Fig. 1

Optimization procedure

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Fig. 2

Close-up view of the NACA0012 airfoil grid

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Fig. 3

CL history of NACA0012 airfoil at Re = 10,000 and α = 6 deg

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Fig. 4

Comparison of the time-averaged lift coefficients of NACA0012 airfoil with the experimental data

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Fig. 5

Comparison of the time-averaged lift coefficients of NACA64A010 airfoil with the experimental data

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Fig. 6

Comparison of the time-averaged drag coefficients of NACA64A010 airfoil with the experimental data

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Fig. 7

Comparison of the baseline and optimized configuration

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Fig. 8

History of the time-averaged lift and drag coefficients during optimization

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Fig. 9

Comparison of the immediate lift coefficient between baseline and optimized configuration

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Fig. 10

Comparison of the immediate drag coefficient between baseline and optimized configuration

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Fig. 11

Comparison of the immediate lift to drag ratio between baseline and optimized configuration




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