200624th AIAA Applied Aerodynamics ConferenceRequires access

Aerodynamic Shape Optimization Based on Drag Decomposition

Wataru Yamazaki, Kisa Matsushima, Kazuhiro Nakahashi

Open publisher page 10 citations

Abstract

An advanced drag prediction method, mid-field drag decomposition method is applied in aerodynamic shape optimization problems. The drag decomposition method decomposes total drag into wave, profile, induced and spurious drag component, the latter resulting from the effect of numerical diffusion included in CFD results. Hence the more accurate drag prediction can be achieved by the elimination of the spurious drag component. This method is applied in transonic airfoil, planform and winglet shape optimizations. As the optimizer and flow solver, genetic algorithm and Euler/NS simulation are used, respectively. The results show that the optimizations based on the drag decomposition method are reliable and accurate. Moreover, precise investigation of the drag reduction mechanisms is achieved by using the drag decomposition method.

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What this paper is about

An advanced drag prediction method, mid-field drag decomposition method is applied in aerodynamic shape optimization problems. The drag decomposition method decomposes total drag into wave, profile, induced and spurious drag component, the latter resulting from the effect of numerical diffusion included in CFD results. Hence the more accurate drag prediction can be achieved by the elimination of the spurious drag component. This method is applied in transonic airfoil, planform and winglet shape optimizations. As the optimizer and flow solver, genetic algorithm and Euler/NS simulation are used, respectively. The results show that the optimizations based on the drag decomposition method are reliable and accurate. Moreover, precise investigation of the drag reduction mechanisms is achieved by using the drag decomposition method.

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Available abstract

An advanced drag prediction method, mid-field drag decomposition method is applied in aerodynamic shape optimization problems. The drag decomposition method decomposes total drag into wave, profile, induced and spurious drag component, the latter resulting from the effect of numerical diffusion included in CFD results. Hence the more accurate drag prediction can be achieved by the elimination of the spurious drag component. This method is applied in transonic airfoil, planform and winglet shape optimizations. As the optimizer and flow solver, genetic algorithm and Euler/NS simulation are used, respectively. The results show that the optimizations based on the drag decomposition method are reliable and accurate. Moreover, precise investigation of the drag reduction mechanisms is achieved by using the drag decomposition method.

Key concepts: Drag, Drag divergence Mach number, Wave drag, Lift-induced drag, Airfoil, Drag coefficient, Parasitic drag, Aerodynamic drag

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