Please wait a minute...
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2012, Vol. 13 Issue (2): 105-120    DOI: 10.1631/jzus.A1000502
Mechanics and Mechanical Engineering     
Kinematic optimization of 2D plunging airfoil motion using the response surface methodology
Mahmoud Mekadem, Taha Chettibi, Samir Hanchi, Laurent Keirsbulck, Larbilabraga
Fluids Mechanics Laboratory, Polytechnic Military School, Bordj el Bahri, Algiers 16045, Algeria; Structural Mechnics Laboratory, Polytechnic Military School, Bordj el Bahri, Algiers 16045, Algeria; TEMPO Laboratory, University of Valenciennes and Hainaut-Cambresis, 59313 Valenciennes Cedex 9, France
Download:     PDF (0 KB)     
Export: BibTeX | EndNote (RIS)      

Abstract  The propulsive efficiency of a plunging NACA0012 airfoil is maximized by means of a simple numerical optimization method based on the response surface methodology (RSM). The control parameters are the amplitude and the reduced frequency of the harmonic sinusoidal motion. The 2D unsteady laminar flow around the plunging airfoil is computed by solving the Navier-Stokes equations for three Reynolds number values (Re=3.3×103, 1.1×104, and 2.2×104). The Nelder-Mead algorithm is used to find the best control parameters leading to the optimal propulsive efficiency over the constructed response surfaces. It is found that, for a given efficiency level and regardless of the considered Re value, it is possible either to obtain high thrust by selecting a high oscillation frequency or to reduce the input power by adopting a low plunging amplitude.

Key wordsPlunging airfoil      Propulsive efficiency      Optimization      Response surface methodology (RSM)     
Received: 11 December 2010      Published: 18 January 2012
CLC:  TK83  
Cite this article:

Mahmoud Mekadem, Taha Chettibi, Samir Hanchi, Laurent Keirsbulck, Larbilabraga . Kinematic optimization of 2D plunging airfoil motion using the response surface methodology. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2012, 13(2): 105-120.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.A1000502     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2012/V13/I2/105

[1] Peng Guo, Jun-hong Zhang. Numerical model and multi-objective optimization analysis of vehicle vibration[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2017, 18(5): 393-412.
[2] Tian-tian Zhang, Wei Huang, Zhen-guo Wang, Li Yan. A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(8): 632-645.
[3] Hossein Rezaei, Ramli Nazir, Ehsan Momeni. Bearing capacity of thin-walled shallow foundations: an experimental and artificial intelligence-based study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(4): 273-285.
[4] Bao-tong Li, Su-na Yan, Jun Hong. A growth-based topology optimizer for stiffness design of continuum structures under harmonic force excitation[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 933-946.
[5] Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun . A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 961-973.
[6] Jin Cheng, Ming-yang Tang, Zhen-yu Liu, Jian-rong Tan. Direct reliability-based design optimization of uncertain structures with interval parameters[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(11): 841-854.
[7] Liang Ye, Yin-fu Jin, Shui-long Shen, Ping-ping Sun, Cheng Zhou. An efficient parameter identification procedure for soft sensitive clays[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(1): 76-88.
[8] Antoine Dumas, Jean-Yves Dantan, Nicolas Gayton, Thomas Bles, Robin Loebl. An iterative statistical tolerance analysis procedure to deal with linearized behavior models[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(5): 353-360.
[9] Qing-long Meng, Xiu-ying Yan, Qing-chang Ren. Global optimal control of variable air volume air-conditioning system with iterative learning: an experimental case study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(4): 302-315.
[10] Lei Fu, Zhen-ping Feng, Guo-jun Li, Qing-hua Deng, Yan Shi, Tie-yu Gao. Experimental validation of an integrated optimization design of a radial turbine for micro gas turbines[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(3): 241-249.
[11] Wei Wei, Ang Liu, Stephen C. Y. Lu, Thorsten Wuest. A multi-principle module identification method for product platform design[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(1): 1-10.
[12] Abbas Al-Refaie. Applying process analytical technology framework to optimize multiple responses in wastewater treatment process[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(5): 374-384.
[13] Chang-yu Cui, Bao-shi Jiang, You-bao Wang. Node shift method for stiffness-based optimization of single-layer reticulated shells[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(2): 97-107.
[14] Yi-cong Gao, Yi-xiong Feng, Jian-rong Tan. Multi-principle preventive maintenance: a design-oriented scheduling study for mechanical systems[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(11): 862-872.
[15] Jin Cheng, Gui-fang Duan, Zhen-yu Liu, Xiao-gang Li, Yi-xiong Feng, Xiao-hai Chen. Interval multiobjective optimization of structures based on radial basis function, interval analysis, and NSGA-II[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(10): 774-788.