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Comparative study on analytical and computational aerodynamic models for flapping wings MAVs

Published online by Cambridge University Press:  07 July 2020

M.F. Valdez*
Affiliation:
Facultad de Ingeniería and Instituto de Investigaciones en Energía no Convencional, Universidad Nacional de Salta and CONICET, Salta, Argentina
B. Balachandran
Affiliation:
Department of Mechanical Engineering, University of Maryland College Park, MD, 20742, USA
S. Preidikman
Affiliation:
Instituto de Estudios Avanzados en Ingeniería y Tecnología (IDIT), Universidad Nacional de Córdoba and CONICET, Córdoba, Córdoba, 5000, Argentina
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Abstract

A range of quasi-steady and unsteady aerodynamic models are used to predict the aerodynamic forces experienced by a flapping wing and a detailed comparison amongst these predictions in provided. The complexity of the models ranges from the analytical potential flow model to the computational Unsteady Vortex Lattice Method (UVLM), which allows one to describe the motion of the wake and account for its influence on the fluid loads. The novelty of this effort lies in a modification of the predicted forces as a generalisation of the leading edge suction analogy. This modification is introduced to account for the delayed stall mechanism due to leading edge flow separation. The model predictions are compared with two sets of independent experimental data and with computational fluid dynamics (CFD) simulation data available in the literature. It is found that both, the modified analytical model and the UVLM model can be used to describe the time history of the lift force, in some cases with better results than a high-fidelity CFD model. The models presented here constitute a useful basis for the aerodynamic design of bioinspired flapping-wings micro-air vehicles.

Information

Type
Research Article
Copyright
© The Author(s) 2020. Published by Cambridge University Press on behalf of Royal Aeronautical Society
Figure 0

Figure 1. Two-dimensional elliptic body $\mathcal{E}$ undergoing prescribed translation and rotation. (a) Conformal map of a circle into an ellipse. (b) ULVM discretization.

Figure 1

Figure 2. Summary of quasi-steady drag and lift coefficients $C_d$ and $C_l$ as a function of the angle-of-attack obtained with the different methodologies presented.

Figure 2

Table 1 Comparison between $C_d$ predictions, experiments and CFD(24) for different values of $\psi$. Highlighted cells are the best SS4 values

Figure 3

Table 2 Comparison between $C_l$ predictions, experiments and CFD(24) for different values of $\psi$. Highlighted cells are the best SS4 values

Figure 4

Figure 3. Normalised drag and lift for a delayed rotation flapping kinematic $\phi\,\text{=}$ –45.0deg.

Figure 5

Figure 4. Normalised drag and lift for a symmetric rotation flapping kinematic $\phi\,\text{=}$ 0.0deg. Line references from Fig. 3.

Figure 6

Figure 5. Normalised drag and lift for a advanced rotation flapping kinematic $\phi\,\text{=}\,\text{45.0}\text{deg}$. Line references from Fig. 3.

Figure 7

Figure 6. Taylor diagrams summarising the error analysis of the models and CFD in the prediction of the aerodynamic load coefficients. Red: $\psi\,\text{=}$ –45deg, blue: $\psi\,\text{=}$ 0deg, green: $\psi\, \text{=} $ 45deg. $\star$: CFD(24), $+$:UVLM, $*$: UVLM $\varrho\,\text{=}\,0$, $\otimes$: UVLM $\varrho\,\text{=}\,1$, $\square$: Potential, $\triangle$: Model $\varrho\,\text{=}\,0$, $\lozenge$: Model $\varrho \,\text{=}\, 1$. Filled markers: Quasi-Steady. (a) $C_d$. (b) $C_l$.

Figure 8

Figure 7. Wakes generated by a flat plate with kinematics (36) with delayed (left), symmetric (center) and advanced (right) rotation motion. From top to bottom, the instants of nondimensional time $f_f t$ shown are approximately: 1.00, 1.125, 1.375, 1.625, 1.875 and 2.00.

Figure 9

Table 3 Values of the Coefficients in Equation (38)

Figure 10

Figure 8. Flapping wing with a two-dimensional wing section at distance r highlighted. (a) Three-dimensional flapping wing. (b) Schematic planform of a wing.

Figure 11

Figure 9. Comparison between normalised lift predicted by the models and the experimental data.

Figure 12

Table 4 Comparison between $C_l$ predictions of the models and Dickinson et al (7) experiments. Highlighted cells are the best SS4 values

Figure 13

Figure 10. Wakes generated by a flat plate with kinematics (38) with delayed (left), symmetric (centre) and advanced (right) rotation. From top to bottom, the instants of nondimensional time $f_f t$ shown are approximately: 1.000, 1.125, 1.250, 1.375, 1.500, 1.625, 1.750, 1.875 and 2.000.

Figure 14

Figure 11. Taylor diagram summarising the error analysis of normalised $C_l$ predictions of the models. Refer to Fig. 6(a) for color and mark references.

Figure 15

Figure A.1. Drag (left) and Lift (right) coefficients as a function of the angle-of-attack obtained with the (unmodified) UVLM model at different nondimensional times $t_{v} V/c$.

Figure 16

Figure A.2. Drag (left) and Lift (right) coefficients as a function of the angle-of-attack obtained with the UVLM model with $\varrho\,\text{=} \,\text{0}$ at different nondimensional times $t_{v} V/c$.

Figure 17

Figure A.3. Drag (left) and Lift (right) coefficients as a function of the angle-of-attack obtained with the UVLM model with $\varrho\,\text{=}\,\text{1}$ at different nondimensional times $t_{v} V/c$.