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Research Papers: Flows in Complex Systems

Multiobjective Design Study of a Flapping Wing Power Generator

[+] Author and Article Information
Eriko Shimizu

Department of Mechanical Engineering, Toyo University, Kujirai 2100, Kawagoe, Saitama 350-0815, Japanshimizu@eng.toyo.ac.jp

Koji Isogai

Department of Aerospace Engineering, Nihonbunri University, 1727 Ooaza Ichigi, Ooita 870-0397, Japanisogai@nbu.ac.jp

Shigeru Obayashi

Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi 980-8577, Japanobayashi@ifs.tohoku.ac.jp

J. Fluids Eng 130(2), 021104 (Jan 24, 2008) (8 pages) doi:10.1115/1.2829580 History: Received July 07, 2006; Revised September 04, 2007; Published January 24, 2008

In conventional windmills, the high tip speed creates aerodynamic noise, and when they are used at very low Reynolds numbers, their performance deteriorates due to laminar separation. These are important issues in modern windmills. Present study deals with a new windmill concept, the “flapping wing power generator,” which would solve such problems. The concept is to extract energy via the flutter phenomena and the concept has been developed by some researchers. In 2003, Isogai2003, “Design Study of Elastically Supported Flapping Wing Power Generator  ,” International Forum on Aeroelasticity and Structural Dynamics, Amsterdam) proposed a new system. The system utilizes dynamic stall vortices efficiently and generates high power. The dynamic stall vortex is something that should be avoided in conventional windmills. They optimized the system to maximize the efficiency and obtained the set of design parameters, which achieved best efficiency. The system works at low frequencies and it enables high efficiency. To realize the system, it is necessary to consider the power and the efficiency. Thus, the present study optimized the system to maximize both the power and the efficiency. To obtain nondominated solutions, which are widely distributed in the design space, adaptive neighboring search, which is one of evolutionary algorithms, has been extended to handle multiple objectives and was used in the present study. Self-organizing map was used for the data mining. The trade-off between the power and the efficiency has been visualized. The trade-off curve was shaped by the constraints on the reduced frequency and the phase delay angle, which were imposed so that the dynamic stall phenomenon gives favorable effects on the power generation. The heaving amplitude was a parameter correlated to the objective functions. The reduced frequency and the phase delay angle change to control the heaving amplitude. Consequently, when the power is emphasized, the system undergoes a large heaving motion with a low frequency. On the other hand, when the efficiency is emphasized, the system undergoes a small heaving motion with a high frequency. Multiobjective optimization and data mining revealed the trade-off of the objective functions and the parameters correlated to the objective functions. The power obtained was comparable to that of present windmills at low tip-speed ratio region.

Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Concept of flapping wing power generator

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Figure 2

Geometric definition of flapping wing power generator

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Figure 3

Computational mesh around the airfoil

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Figure 4

Nondominated solutions plotted by power and efficiency

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Figure 5

SOM clustered and colored by objective functions: (a) power W and (b) efficiency η

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Figure 6

SOM clustered by objective functions and colored by output variables: (a) dimensionless heaving amplitude h0* and (b) phase delay angle ϕ

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Figure 7

SOM clustered by objective functions and colored by design variables: (a) axis of pitch a*, (b) reduced frequency k, (c) damping coefficient a*, (d) mass ratio μ, and (e) frequency ratio ωh∕ω

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Figure 8

Nondominated solutions plotted by damping coefficient and mass ratio colored by phase delay angle

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Figure 9

Nondominated solutions plotted by frequency ratio and mass ratio colored by phase delay angle

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Figure 10

Nondominated solutions plotted by damping coefficient and frequency ratio colored by phase delay angle

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Figure 11

Representative eight nondominated solutions plotted by the power and the efficiency. Circles show the solutions obtained by analytical evaluation and squares show the solutions recalculated by numerical evaluation.

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Figure 12

Flow field (isovorticity contours) around the wing of the system: (a) ωt=π∕24, (b) ωt=7π∕24, (c) ωt=13π∕24, and (d) ωt=19π∕24

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Figure 13

Eight nondominated solutions plotted by dimensionless heaving amplitude and efficiency. Circles show the solutions obtained by analytical evaluation and squares show the solutions recalculated by numerical evaluation.

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Figure 14

Eight nondominated solutions plotted by phase delay angle and power. Circles show the solutions obtained by analytical evaluation and squares show the solutions recalculated by numerical evaluation.

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Figure 15

Comparison with other types of windmill

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