Sage Journals: Discover world-class research

Abstract

It is a challenge to explore the unsteady vortex structures of flexible flapping wings of X-shaped flapping-wing micro air vehicles (also known as clapping-wing micro air vehicles (CWMAVs)). The objective of this paper is to obtain the influence of wind speed, flapping frequency, and angle of attack (AoA) on the instantaneous and average force coefficients of CWMAVs, investigate flow visualization of the leading-edge vortex (LEV), trailing-edge vortex (TEV) and wake vortex (WV) structures and identify some novel flow mechanisms of flapping propulsion. This paper proposes a mechanics and particle image velocimetry (PIV) measuring platform in a low-speed tunnel. In addition, cross-correlation peak analysis and kriging image reconstruction are applied for postprocessing to enhance PIV image recognition. Combining the time evolution of the forces, the force coefficients, and the flow visualization, we find the evolution and effects of LEV, TEV and WV structures.

Keywords

Clapping-wing micro air vehicles instantaneous and average forces particle image velocimetry unsteady vortex structures high-lift and high-thrust mechanisms

Introduction

Studies of micro air vehicles (MAVs) have attained a new level of detail over the last several decades, where MAVs can be employed for aerial activities to security missions in hazardous and physically inaccessible regions.^1–3 As MAVs feature high maneuverability and flight efficiency, issues of cruising and dexterity have been well resolved. Compared with the conventional propulsion systems of MAVs, an increasing interest in flapping flight has been seen in recent years due to rapid development in mechanics and measurement techniques among biological and aerospace scientific spheres.^4,5 The observation of the natural flapping flight of birds and insects has provided tremendous inspiration for the aeronautical development of MAVs. Therefore, the design of the flapping-wing micro air vehicle (FWMAV) emerge at the right moment with flapping-wing concepts .^6–8

Unstable flow structures are known to inseparably influence the aerodynamic performance of all types of MAVs. It is certainly necessary to explore flow phenomena to fully develop MAVs.^9–11 Especially for flapping flight, the extraordinary flight capabilities of flyers benefit from their unique flow structures, this research field is called flapping-wing propulsion or inspired propulsion.^12–15 Flapping-wing propulsion, which leads to superior aerodynamic performance, is generally studied by means of numerical calculations and experiments. However, the numerical simulation of flapping flight involves high-frequency motion and flexible wings, which bring infinite challenges to achieving convergence. Moreover, experimental verification is an extremely efficient process to support numerical analysis.^16,17 A summarized experimental research approaches toward the development of ornithopter- and insect-inspired MAVs have been listed.¹⁸ Different flight modes, wing planform, wingspan, velocity ranges, test methods, and specification methods have been considered by researchers to figure out flapping propulsion. Besides, it is worth mentioning that limited research is available on small-scale FWMAVs, wing-wing effects of clapping wings, and unsteady vortex mechanisms.

Aerodynamic experiments have accelerated the research progress of flapping-wing propulsion.^19,20 Kolomenskiy et al.²¹ evaluated aerodynamic force generation of a small insect capacity using a combined experimental and numerical approach. Particle image velocimetry (PIV), as the main experimental means of quantitative visualization techniques, has become a powerful tool to clearly recognize flapping-wing propulsion.^15,22–25 Extensive experiments utilizing PIV techniques have been carried out to first find a better understanding of the flow mechanism of flyers, including birds and insects.^26–28 Krishna et al.²⁹ investigated the effect of pitch on the evolution of flow and aerodynamic forces around a hovering flat-plate wing by particle image velocimetry and direct force measurements. Fuchiwaki et al.³⁰ conducted a particle image velocimetry measurement around the flapping butterfly wing of a butterfly and investigated the vortex structure of the wing and its dynamic behavior. Subsequently, many experiments have naturally followed to study the unsteady flow structures of FWMAVs and inspired mechanical systems. Lankford et al.³¹ combined the force and flowfield measurements and computational fluid dynamics analysis to understand unsteady aerodynamic mechanisms and their relation to force production and aerodynamic efficiency on a rigid wing of FWMAV. Zhao et al. ³² visualized the flows on wings of varying flexural stiffness of FWMAV using a custom 2D PIV system, while simultaneously monitoring the magnitude of the aerodynamic forces. Through protracted and unremitting efforts, many unsteady effects have been found associated with separated flow structures, supporting the possible advantages of flapping-wing propulsion. In general, four unsteady flow mechanisms have definitely been present: (1) build-up of a starting vortex from the growth of the trailing-edge vortex (TEV), i.e., the Wagner effect; (2) delayed stall and leading-edge vortex (LEV); (3) rotational circulation around a rotating surface, i.e., the Kramer effect; and (4) capture of the wake of the previous stroke by the subsequent stroke, i.e., wake capture.¹⁵

Various attachment vortices, including the LEV and TEV, are extremely important during the flapping flight cycle.³³ The LEV is generally believed to be the most influential factor in flapping-wing aerodynamics. The stability and size of the LEV highly impact the aerodynamic performance, which is strongly influenced by the Reynolds number (Re).³⁴ The span vibration increases the vortex flow energy and brings the LEV closer to the upper surface, which in turn increases the LEV stability.³⁵ Considering the importance of flexibility, the flexibility distribution, rigid structure of the front chord and flexible structure of the rear chord are known to be beneficial to lift and thrust generation due to the adjustment of the LEV.³⁶ Moreover, rapid wing rotation at the beginning and end of the downstroke and upstroke can enhance the lift or thrust in flapping flight by influencing LEV.³⁷ Added mass, a reactive noncirculatory force, generates a reactive force to accelerate the surrounding air to bring high lift by changing the structure of LEV.³⁸ These notable studies further prove the important role of LEV. In addition to the LEV mechanism of flapping wings, the wake vortex (WV) also plays a significant role in the generation of force.^17,39

To break the limit of the numerical model of flapping-wing propulsion, experimental exploration is a more credible and reliable method, and PIV experiment can provide more quantitative information on the characterization of the vortex structure. The existing studies mainly focus on rigid wings, and it is difficult to combine force measurement with flow field measurement. In addition, research on flapping frequency, wind speed, and angle of attack for clapping-wing type MAV has not been sufficiently studied. Considering the aforementioned reasons, it is necessary to carry out a PIV experiment on unsteady flow structure and mechanical data of a clapping-wing micro air vehicle (CWMAV) to explore more unsteady aerodynamic mechanisms.

Our work focuses on the following objectives: how flow speed, flapping frequency, and AoA affect the forces and force coefficients on CWMAV, together with flow visualization; and the underlying flow mechanism of flapping flight. Three main key parameters are considered in our experiment to support the mechanical design and optimization of CWMAVs, and the different design strategies are compared. After obtaining the LEV and TEV visualization, the novel high lift and thrust mechanisms behind the strong fluid-structure interaction are explored in combination with the vorticity contour and time evolution of the forces.

There are plenty of interesting challenges involved in acquiring the desired data. The initial challenge to be overcome is to ensure that test prototypes keep similar performance under the same conditions (same flapping frequency, angle of attack, and wind speed) during the experiment. The next difficulty involves interference from the device and the environment. This challenge mainly refers to ambient light, reflected light from the wings, and mechanical vibration of devices. Another big challenge involves how to capture the entire and clear flow field, the camera needs to be placed in a proper position, the laser needs to be placed at a proper angle to generate the laser sheet, and the camera and imaging surface also need a good distance and angle to ensure that the correct particles are captured. The performances (including resolution, sampling frequency, etc) of the high-speed camera and the mechanical sensor are also highly correlated to the success of our experiment. Moreover, another issue that should be carefully considered is how to improve image quality. This problem involves how to get enough illuminators for the particles, how to carry out separate measurements of the leading edge vortex and the trailing edge vortex, and how to make image post-processing which enables velocity vectors and vortex structure to be accurately identified. The relative technology for better image quality mainly includes image reconstruction, damage detection, and inherent distortion disturbance analysis.⁴⁰

In general, a strong agreement with unsteady mechanisms is found, especially for the delayed stall and added mass of the Weis-Fogh mechanism. However, some differences are also found, especially for the jet effects on thrust and the novel evolutions between LEVs and TEVs.

Experimental methodology

Wind tunnel and test model

Considering the difficulty in accurate control of the CWMAV, we adopt an experiment under a tethered configuration as our strategy. Qualitative smoke visualization has proved instrumental in revealing particular flow structures. Then, we disclose a novel PIV measurement system for the flow field of the CWMAV, which comprises a test model, a clamping regulator, a wind tunnel, a mechanical data acquisition system and a PIV system (Figure 1). All measuring instruments are coordinated by means of synchronizers.

Figure 1.

PIV system of the CWMAV.

The subject of investigation for the current paper is a bioinspired CWMAV designed and built at the University of Electronic Science and Technology of China. The CWMAV has a biplane wing configuration with wings that consist of polyethylene (PE foil) (Figure 2(a)) reinforced with carbon rods as veins. It has a total wingspan of 280 mm and weighs 17 g. The flapping motion driving mechanism includes a hand-made brushless motor with a motor controller, a gear system and a double crank-double rocker mechanism, which is shown in Figure 2(b). Our CWMAV can hover as well as fly in the forward and backward directions with the configuration shown in Table 1. Figure 3 presents the wing kinematic profile adopted in this study. The aircraft clamping regulator is located at the bottom of the CWMAV, has the function of fixing the MAV and adjusting the AoA and location and is equipped with a control signal input device.

Figure 2.

Test model. (a) Visualization of the flapping cycle represented by high-speed camera recordings. (b) Gear system and double crank-double rocker mechanism.

Figure 3.

Flapping kinematics.

Table 1.

Kinematic parameters of the mechanism.

$l_{0}$ , mm	$l_{1}$ , mm	$l_{2}$ , mm	$l_{3}$ , mm	$A_{0}$ , mm	$A_{1}$ , mm	$Φ_{f, u}$ , deg	$Φ_{f, l}$ , deg	$Φ_{f}$ , deg
17.09	2.30	13.00	9.00	16.00	6.00	46.71	26.78	10

The experiments were conducted in a low-speed wind tunnel (Figure 4). This is a closed-circuit facility with a rectangular cross section 1.2 m wide, 1.2 m high, and 3 m long. The entrance section is equipped with a regular hexagonal honeycomb and a 5-layer 24 mesh/inch damping net. The 4 corners of the wind tunnel are installed with 8 baffles. The fan in the power section of the wind tunnel has a diameter of 0.8 m and is composed of 8 blades. It is driven by a variable frequency speed motor, and the rated speed of the motor is 986 r/min. Prior to the test section, the tunnel has an entry section with screens and a contraction ratio of 5:1 to ensure that the angle of wind deflection is lower than 0.5 degrees and the turbulence level is lower than 0.5%. The tunnel flow speed was monitored by a pitot tube installed in the tunnel, and the freestream speed was controlled by a manual speed controller that drove the fan of the tunnel, providing an experimental flow speed from 0.1 m/s to 5 m/s, which was also measured by a pitot tube. The mechanical data acquisition system includes a six-dimensional mechanical sensor ( $F_{x}, F_{y} = 8 N, F_{z} = 14 N, M_{x}, M_{y}, M_{z} = 0.05 Nm, ATI - Nano 17$ ), a data acquisition card (National Instruments, NI) and PC terminal mechanical data acquisition software.

Figure 4.

Low-speed wind tunnel.

PIV experimental setup

The whole PIV image capture system includes a charge-coupled device (CCD) high-speed camera (85 mm, 8000 Hz, $1024 \times 1024 pixels$ , Phantom 7.3, TRI America, Figure 5(a)), a high-frequency laser (532 nm, 200 mJ, $2560 \times 2160 pixels$ , ILA Germany, Figure 5(b)), a PIV synchronization controller, some optical components, and image data acquisition software. The CCD high-speed camera, high-frequency laser, and image acquisition software are coordinated and controlled by the PIV synchronization controller. The PIV synchronization controller and the CWMAV synchronization controller are utilized separately using a PC. All images collected by the CCD high-speed camera are transmitted to the computer for storage and analysis. Our test model is placed in the wind tunnel, as shown in Figure 5(c). The working diagram of the whole PIV image acquisition module is shown in Figure 5(d).

Figure 5.

PIV instruments. (a) CCD high-speed camera. (b) High-frequency laser generator. (c) Positioned test model. (d) Diagram of laser irradiation.

There are some uncertainties in the experiment, mainly divided into environmental uncertainty and structural uncertainty. The environmental uncertainty mainly includes the wind speed uncertainty caused by uncontrollable turbulence and slight fluctuations in wind speed at ultra-low speeds and the AoA and frequency uncertainty caused by flapping model vibration and fixed instrument vibration. The structural uncertainty mainly comes from the manufacturing error of the components, the assembly error process, the fatigue of the mechanism and the motor. To eliminate the interference of these uncertainties in our experiments, the main measures we take include secondary measurement of the wind speed in each experiment to ensure that the wind speed is stable and meets the value requirements; strengthening the stability of the fixed platform; and using an oscilloscope for pre-detection to ensure that each test model in experiments has similar mechanical properties. Generally, the rest of the uncertainty is proven to have little impact on the results, so it is not our consideration in this study.

These PIV experimental setups can both measure the flow field around the CWMAV and collect the aerodynamic force/aerodynamic torque during the whole flapping cycle. Subsequently, we obtain velocity and mechanical data for further comparison and analysis.

Results and discussions

Instantaneous aerodynamic force measurements

We first use a Nano-ATI 17 to acquire mechanical data and utilize a Chebyshev II filter to perform data postprocessing. Based on the working and experimental conditions of the CWMAV, we set the sampling frequency to 10,000 Hz, the filter cut-off frequency to 40 Hz, and the filter order to 5. To extend the applicability of the results to the same types of CWMAV, forces are non-dimensionalized by average lift and average thrust coefficient ( $c_{L} = L / (ρ U_{t i p}^{2} S) and c_{D} = D / (ρ U_{t i p}^{2} S)$ ), where L and D are the lift and thrust value respectively, $U_{t i p}$ is the mean wingtip velocity, S is the area of each wing, and $ρ$ represents the density of air). The time course of lift coefficient and thrust coefficient for the whole CWMAV under a frequency of 16 Hz, an incoming flow speed of 3.5 m/s and an AoA of 15 degrees is shown in Figure 6 for the 5th cycle (the region bounded by the red line is a period).

Figure 6.

Time evolution of the instantaneous aerodynamic force. (a) Time evolution of lift coefficient. (b) Time evolution of thrust coefficient.

We combine some classic flapping-wing high-lift mechanisms through the change in instantaneous force, which not only verifies the correctness of our measurement but also lays the foundation for our follow-up discussion and analysis of the forces. Figure 6 shows that there are two lift peaks during the out-stroke (from $t = 0.06125 s$ to $t = 0.0925 s$ ), which are generally referred to as the reversal wake capture effect and the added mass effect. There is a higher lift peak during the in-stroke before the out-stroke phase, which is generally due to the strong LEV effects. The reason why the lift maintains a relatively high and stable value in the middle of the in- and out-stroke is the delayed stall mechanism. This tendency has been recognized to be the unique characteristic of flapping propulsion, which can prove to some extent that our experimental data are theoretically convincing and that our test model is worth further exploration.

Average aerodynamic force measurements

After verifying the correctness of the instantaneous data, we consider the influence of three key influencing factors (wind speed, flapping frequency and AoA) on the average lift coefficient and thrust coefficient during the flight of the CWMAV. The three factors determine whether the CWMAV has enough lift and thrust for flight. Through our force research, the ways in which these parameters affect the aerodynamic characteristics of the CWMAV are determined, and the parameter settings that can support flight are established. In addition, these investigations of the average force are also the contrast and basis for the investigation of the flow field structure.

Figure 7(a) shows the average of the $5 th - 10 th$ cycles, describing the influence of wind speed on the average lift coefficient and thrust coefficient. When setting the frequency ( $F$ ) to 16 Hz and the AoA to 15 degrees, the average lift coefficient first rises rapidly with increasing wind speed, then rises to a steady state and finally rises rapidly again. The effect of the wind speed on the lift coefficient is strongest for wind speed ( $U$ ) at 5.5 m/s. The magnitude of the average thrust coefficient is inversely proportional to the wind speed. Since force coefficients are directly related to both flapping frequency and force, flapping frequency effects are firstly compared with average lift and thrust value shown in Figure 7(b). At constant $U = 3.5 m / s$ and $AoA = 15 \deg$ , the average lift is observed to first rise rapidly and then decrease as the frequency rises, reaching a peak at approximately 12 Hz. The average thrust value has little relationship with the frequency and remains at approximately 0.1 N. However, Figure (c) indicates that as the flapping frequency increases, the force coefficients decrease, revealing that the force evolution is less-than-quadratic with the flapping frequency. Figure 7(d) shows the influence of the AoA on the average lift coefficient and thrust coefficient. This shows a similar tendency in behavior with frequency. At constant $U = 3.5 m / s$ and $F = 16 Hz$ , there is a sharp increase before 30 degrees. Then, it remains relatively stable as the AoA rises, reaching a peak after approximately 30 degrees.

Figure 7.

Evolution of the averaged lift coefficient and thrust coefficient. (a) Influence of the wind speed. (b) Influence of the frequency (averaged lift and thrust). (c) Influence of the frequency. (d) Influence of the AoA.

Flow visualization

Analyzing the influence of various factors on the flow field of the CWMAV is another main purpose of our research. Through this analysis, the aerodynamic characteristics of the CWMAV can be further explored, and the most optimized design can be carried out. The processing of the raw particle image pairs begins with a background subtraction algorithm based on proper orthogonal decomposition. In a similar implementation in our research, we utilize the following main principles: record two tracer particle positions in a very short time $(Δ t = t_{1} - t_{2})$ using high-speed cameras. From the image analysis, the particle displacement was obtained (namely, $Δ x and Δ y$ ). Through the particle displacement and exposure time interval ( $Δ t$ ), the velocity vector of each point in the flow field $Δ V$ can be calculated by $v_{x} = lim_{t_{2} \to t_{1}} \frac{X_{2} - X_{1}}{t_{2} - t_{1}}$ and $v_{y} = lim_{t_{2} \to t_{1}} \frac{Y_{2} - Y_{1}}{t_{2} - t_{1}}$ . Other flow parameters can be calculated based on the velocity of particles (including the vorticity diagram of the flow field, velocity component diagram, flow diagram, and swirl diagram).

Table 2 shows selected important PIV experimental parameter values. By utilizing high-precision and high-efficiency PIV technology, we conduct a comprehensive experimental exploration of the flow field. The evolution of the LEV and TEV for each case is documented in this section. The evolution of the flow is broken down into two parts: the LEV and TEV. To identify the respective roles of the LEV and the TEV, we trace the flow fields near the leading edge (image view size: $200 \times 200 m m^{2}$ ) and trailing edge (image view size: $400 \times 400 m m^{2}$ ). We conduct a larger image field of the trailing edge because the area with sharp changes in the wake is much larger.

Table 2.

PIV experimental parameter settings.

Modules	Parameters	Value
High-speed camera	Resolution ratio	$1024 \times 1024 pixels$
	Image field	$\approx 200 \times 200 m m^{2}$ (leading edge) $\approx 400 \times 400 m m^{2}$ (trailing edge)
	Focal length	85 mm
	Aperture	5.6
	Acquisition frequency	2000 Hz
High-frequency laser	Pulse interval	$150 μ s - 1000 μ s$
	Laser	532 nm, 30 mJ
	Laser sheet thickness	2.5 mm ± 0.5 mm
Tracer particles	Smoke particles diameter	2 μm
Image postprocessing	Access window	$64 \times 64 pixels$
	Window overlap	25%
	Window size of median filter	$3 \times 3 pixels$

Our fundamental PIV postprocessing includes cross-correlation analysis of the captured images and correlation as determined using a standard fast Fourier transform (FFT) correlation algorithm, Nyquist-frequency filtering, and the 9-point least-squares peak computing algorithm based on Gauss fitting. However, the measurement results often have a certain deviation due to optical, vibration and various environmental interferences. This makes the tracer particles insufficiently clear, which leads to some points with incorrect velocities. To further avoid the interference of various errors in the measurement, our research introduces a method based on cross-correlation peak analysis to detect the correlation of the identified particles in two adjacent images, as shown in Figures 8(a) and 8(b). In addition, the kriging image reconstruction method is introduced to fill the field that has not been measured due to various interferences and reduce the adverse effect of the error point on the overall velocity distribution so that the velocity field is smoother, as shown in Figures 8(c) and 8(d).

Figure 8.

Cross-correlation peak analysis and kriging image reconstruction. (a) Cross-correlation peak analysis. (b) The correlation of the identified particles. (c) Velocity field smoothing. (d) Error point removal and missing point filling.

Method verification and accuracy

The Weis-Fogh mechanism, which involves the development of the LEV and the TEV near the two clapping wings, is an aspect of classic flapping-wing propulsion theory. The whole flapping cycle can be divided into six phases to show the behavior of the flow structures and their evolution over the flapping cycle. The flapping cycle is defined as starting when the in-stroke is going to start, approaching each other to clap ( $t^{*} = 0 T - 0.5 T$ , where $t^{*}$ is dimensionless time and T represents a period) and flinging apart ( $t^{*} = 0.6 T - 1 T$ ). Figure 9 (black lines show wings, dark arrows show velocity, contour lines show vorticity) shows a flapping cycle of the LEVs and TEVs in our experiment under the similar conditions of the Weis-Fogh mechanism. As illuminated in Figure 9, when folding motion (in-stroke) starts, as the two wings approach each other dorsally, the LEVs generate from outside of the clapping-wings (phase I), and the TEVs also form gradually at phase II. From phase II to phase III, the TEVs shedding from the trailing edge roll up in the form of stopping vortices, and the LEVs also lose strength. Meanwhile, a transfer vortex from the leading edge to the trailing edge is observed (phase III). When the air start to rush in to fill the gap between the two wings (phase IV), an initial boost in circulation is found around the wing system and the LEVs generate inside. Moreover, as the unfolding of the leading edge happens (from phase IV to phase V）, the internal LEVs become stronger and stronger, and the internal LEVs are squeezed to the outside of the wings to support the next generation of the LEVs at the end of the out-stroke (phase VI). By comparing Figure 9 with the Weis-Fogh mechanism, we verified the validity of our experiment, which will fully support follow-up analysis and discussion.

Figure 9.

Flow field structure: experimental structure during a flapping cycle.

Parameter study: effect of some varying parameters on the LEV

Our research aims to analyze the changes in the chordwise two-dimensional LEV and TEV, so we need to decide which spanwise cross section should be selected as our research plane. Therefore, a suitable spanwise position needs to be determined to support all subsequent investigations. As shown in Figure 10, we select 3 typical spanwise positions ( $0.5 R, 0.7 R, and 1.1 R$ ) to place the laser sheet (where R represents the total spanwise length of each wing). We firstly calibrate the three specific positions on the wings corresponding to the three spanwise positions, then make the laser sheet be tangent to the wings of the three positions respectively, and the camera is located a certain distance outside the wingtip for image capture. Through the comparison in Figure 10, we find that: the vortex structure is not fully formed at $0.5 R$ and is in a developing state; at $1.1 R$ , the wingtip vortex is obtained instead of the LEV and TEV which we want to observe; at $0.7 R$ , we could see the clear and separated LEVs and TEVs which can support our follow-up observation experiments. Thus, $0.7 R$ (near the tip of the wings) is selected as the optimal spanwise interface position. Then we can obtain the images during a flapping cycle, as shown in Figure 11.

Figure 10.

LEV during the reversal stroke at different span locations.

Figure 11.

Measured row image around the LEV during a flapping cycle.

To assess the impact of the frequency on the aerodynamic characteristics of the CWMAV, we set $AoA = 15 \deg, U = 0.1 m / s$ as the constant condition and change only the frequency. The evolution of the vortex structures in Figure 12 is characterized by the presence of an attached LEV in the formation and growth stage at $t^{*} = 0.6 T$ . Figure 12 shows that a high-vorticity region has drastically increased in magnitude with respect to this phase due to the increased frequency. Moreover, the attachment time of the LEV increased. The measured force and the flow field comparison can explain why the delayed stall mechanism has a positive effect on lift coefficient.

Figure 12.

LEV analysis during the reversal stroke under different frequencies ( $t^{*} = 0.6 T, AoA = 15 \deg, U = 0.1 m / s$ ).

To determine how the aerodynamic characteristics of the CWMAV are affected by the AoA, we set $F = 16 Hz, U = 0.1 m / s$ as the constant condition we think we are more likely to clearly observe the vortex under this condition. Then, we change only the AoA to perform investigation. Its evolution at $t^{*} = 0.6 T$ (revealing stroke) can be observed in Figure 13. By combining the force evolution, we find that with the changing AoA, the LEV ruptures. The most stable and peak point of the LEV appears when the AoA ranges from 15 to 30 degrees. According to stall angle theory, the LEV becomes more unstable and the lift coefficient decreases after the AoA exceeds 30 degrees.

Figure 13.

LEV analysis during the reversal stroke under different angles of attack ( $t^{*} = 0.6 T, F = 16 Hz, U = 0.1 m / s$ ).

Note that in this case, we do not display images of the impact of wind speed on the LEV. The flow field shows that a high wind speed has little effect on the LEV but makes it difficult to capture the LEV from images in time.

Parameter study: effect of some varying parameters on the TEV

To characterize the flow field around the TEV, a large field of view is observed, as shown in Figure 14. When we explore the TEV under different frequencies, we set $AoA = 15 \deg, U = 0.1 m / s$ as the constant condition and change only the frequency. Figure 15 displays the vorticity for the same timing of the wake under different frequencies. A higher frequency brings a higher TEV strength and a faster vortex moving speed. We also observe the vortex shed along the direction opposite to the free stream, driving the vortex to move along the jet and fall off and dissipate. According to the force evolution mentioned before, the lift is directly proportional to the flapping frequency. This finding leads to a further discussion of whether the TEV strength and the vortex moving speed could affect the lift or thrust of the CWMAV.

Figure 14.

Measured row images around the LEV during a flapping cycle.

Figure 15.

TEV analysis under different frequencies ( $AoA = 15 \deg, U = 0.1 m / s$ ).

To explore the impact of the AoA on the aerodynamic characteristics of the CWMAV, six investigated configurations (−10, 0, 15, 30, 45, and 60 degrees) are compared. We set as the constant condition hypothesized to provide clearest observation of the vortex; then, we change only the AoA to perform an inquiry. Through this exploration, shown in Figure 16, we find that the TEV becomes stronger as the AoA becomes larger, and the wake move fasters; when the AoA reaches 45 degrees or larger, the TEV undergoes structural changes, and the vortex is disrupted.

Figure 16.

TEV analysis under different angles of attack ( $F = 16 Hz, U = 0.1 m / s$ ).

When we explore the influence of the wind speed on the aerodynamic characteristics of the CWMAV, we set $F = 16 Hz, AoA = 15 \deg$ as the constant condition, and then we change only the wind speed to perform the inquiry. By this exploration, shown in Figure 17, we find that as the wind speed increases, the moving speed of the TEV increases, as does the shed rate of the vortex intensity.

Figure 17.

TEV analysis under different wind speeds ( $F = 16 Hz, AoA = 15 \deg$ ).

High-lift and high-thrust mechanisms

In addition to the investigation of the impacts of the flapping frequency, AoA and wind speed on the aerodynamic force and flow field, we address some agreements and differences with existing high-lift and high-thrust mechanisms as follows.

One of the high thrust mechanisms is that high thrust is due to the jet generated by the clapping of the CWMAV. During the out-stroke phase, the leading edges of the wings appear to separate before the trailing edge. This time difference causes a low-pressure zone in the middle of the two flapping wings, and then the surrounding air quickly enters this region to provide energy, as seen in Figure 9. During the in-stroke phase, the airflow quickly extends and produces a much larger thrust due to reactive force, and the jet supports a stable thrust over the whole flapping cycle, as shown in Figure 6(b). This explains why jets generated by clapping wings can directly increase thrust In a deeper study of Figures 7(b) and 15, the model at a higher flapping frequency has a higher vorticity value in the wake visualization, leading to the conclusion that a higher flapping frequency can support a higher thrust by generating a stronger jet.

For the LEV mechanism, in the reverse stroke phase, Figure 6(a) shows that the lift coefficient can still maintain a high steady value. To explain this high lift peak, we found a steadily attached LEV in Figure 9 in this phase. Our experiments confirm that this phenomenon is caused by the delayed stall mechanism. As shown in Figure 9, we further observe that the LEV can be attached stably without shedding and continue to provide a stable high lift during the whole flapping cycle.

For the TEV mechanism, there is always controversy over the formation of TEV in flapping flight. To answer this question, focusing on the upper wing of Figure 9 (because the region from the leading edge to the trailing edge of the lower wing is blocked), we determine that the formation of the TEV mainly originates from the inner LEV, which moves to the trailing edge during the out-stroke. This confirms that the energy of TEV is mainly absorbed from LEV instead of the inlet flow or other types of vortex.

For the TEV mechanism, as the wind speed increases, the LEV is no longer affected, but the lift coefficient still increases, as shown in Figure 7(a). To explain this contradiction, we combine the time evolution of lift coefficient with the experimental results shown in Figure 17. We find that the TEV can be affected by the intension of inlet flow, which accelerates the TEV's propulsion and the shed speed at the end of the in-stroke phase. This phenomenon shows that a higher wind speed can provide more lift coefficient by increasing the TEV's propulsion and the shed speed.

Conclusions

In this study, the effects of some key kinematics on aerodynamic characteristics were found through the measurement of instantaneous and average force coefficients. Moreover, an examination of vorticial structures shows how variations in kinematics affect the development of the LEVs and TEVs on two clapping wings, both independently and simultaneously, while subjected to a uniform flow. Vortex structures were quantitatively visualized through the isocontours of the swirling strength computed from two-dimensional planar (2D-2C) PIV measurements. The core of this study was built around side pair wings of the CWMAV in a wind tunnel, for which this paper has presented measurements documenting the vortex topology and evolution in detail. This study can further serve as a demonstration of its capability for imaging physically challenging flow fields.

Through visual inspection of the results, the evolution of the LEVs and TEVs is clearly understood. Some novel flow mechanisms are discovered to support the design of FWMAVs. As the working principle of our research, the detailed insights into force flow evolution gained in this work can now be leveraged for device strategies to control the aerodynamic loads in a wide range of physical applications, especially for aerodynamic vehicles that rely on the LEVs or TEVs for flight performance.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This work has been supported by the Sichuan Science and Technology Program of China (grant no. 2020JDJQ0036)

ORCID iD

Zhonglai Wang

References

Roshanbin

Altartouri

Karásek

, et al. COLIBRI: a hovering flapping twin-wing robot. Int J Micro Air Veh 2017; 9: 270–282.

Cheng

Sane

Barbera

, et al. Three-dimensional flow visualization and vorticity dynamics in revolving wings. Exp Fluids 2013; 54: 1–12.

Dong

Zhao

. A balance between aerodynamic and olfactory performance during flight in Drosophila. Nat Commun 2018; 9: 1–8.

Yang

Wang

Song

. Dove: a biomimetic flapping-wing micro air vehicle. Int J Micro Air Veh 2018; 10: 70–84.

Karásek

Muijres

De Wagter

, et al. A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns. Science 2018; 361: 1089–1094.

De Wagter

Karásek

de Croon

. Quad-thopter: tailless flapping wing robot with four pairs of wings. Int J Micro Air Veh 2018; 10: 244–253.

Gallar

Van Oudheusden

Sciacchitano

, et al. Large-scale volumetric flow visualization of the unsteady wake of a flapping-wing micro air vehicle. Exp Fluids 2020; 61: 1–21.

Percin

Van Oudheusden

De Croon

, et al. Force generation and wing deformation characteristics of a flapping-wing micro air vehicle ‘DelFly II’ in hovering flight. Bioinspir Biomim 2016; 11: 036014.

Dong

Cheng

. Tip vortices formation and evolution of rotating wings at low Reynolds numbers. Phys Fluids 2020; 32: 021905.

10.

Raghav

Komerath

. Advance ratio effects on the flow structure and unsteadiness of the dynamic-stall vortex of a rotating blade in steady forward flight. Phys Fluids 2015; 27: 2.

11.

Fernandez

Cleaver

Gursul

. Unsteady aerodynamics of a wing in a novel small-amplitude transverse gust generator. Exp Fluids 2021; 62: 1–20.

12.

Liu

Dong

. Vortex dynamics and new lift enhancement mechanism of wing–body interaction in insect forward flight. J Fluid Mech 2016; 795: 634–651.

13.

Kurtulus

. Vortex flow aerodynamics behind a symmetric airfoil at low angles of attack and Reynolds numbers. J Micro Air Veh 2021; 13: 17568293211055653.

14.

Deng

Xiao

Van Oudheusden

, et al. Numerical investigation on the propulsive performance of biplane counter-flapping wings. J Micro Air Veh 2015; 7: 431–439.

15.

Sane

. The aerodynamics of insect flight. J Exp Biol 2003; 206: 4191–4208.

16.

Armanini

Caetano

De Visser

, et al. Modelling wing wake and tail aerodynamics of a flapping-wing micro aerial vehicle. J Micro Air Veh 2019; 11: 1756829319833674.

17.

De Croon

Perçin

Remes

, et al. The delfly. Dordrecht: Springer Netherlands, 2016.

18.

Abas

MFB

Rafie

ASBM

Yusoff

, et al. Flapping wing micro-aerial-vehicle: kinematics, membranes, and flapping mechanisms of ornithopter and insect flight. Chinese J Aeronaut 2016; 29: 1159–1177.

19.

Apker

Corke

. Experiments and modeling of micro flapping wings of different designs in hover. AIAA J 2015; 53: 542–553.

20.

Lyu

Zhu

Sun

. Flapping-mode changes and aerodynamic mechanisms in miniature insects. Phys Rev E 2019; 99: 012419.

21.

Kolomenskiy

Farisenkov

Engels

, et al. Aerodynamic performance of a bristled wing of a very small insect. Exp Fluids 2020; 61: 1–13.

22.

Westerweel

Elsinga

Adrian

. Particle image velocimetry for complex and turbulent flows. Annu Rev Fluid Mech 2013; 45: 409–436.

23.

Ellington

. The aerodynamics of hovering insect flight. IV. Aerodynamic mechanisms. Philos Trans R Soc Lond B 1984; 305: 79–113.

24.

Birch

Dickinson

. Spanwise flow and the attachment of the leading-edge vortex on insect wings. Nature 2001; 412: 729–733.

25.

Lehmann

Sane

Dickinson

. The aerodynamic effects of wing–wing interaction in flapping insect wings. J Exp Biol 2005; 208: 3075–3092.

26.

Chen

Kolomenskiy

Nakata

, et al. Forewings match the formation of leading-edge vortices and dominate aerodynamic force production in revolving insect wings. Bioinspir Biomim 2018; 13: 016009.

27.

Henningsson

Michaelis

Nakata

, et al. The complex aerodynamic footprint of desert locusts revealed by large-volume tomographic particle image velocimetry. J R Soc Interface 2015; 12: 0119.

28.

Ford

Kasoju

Gaddam

, et al. Aerodynamic effects of varying solid surface area of bristled wings performing clap and fling. Bioinspir Biomim 2019; 14: 046003.

29.

Krishna

Green

Mulleners

. Effect of pitch on the flow behavior around a hovering wing. Exp Fluids 2019; 60: 1–17.

30.

Fuchiwaki

Kuroki

Tanaka

, et al. Dynamic behavior of the vortex ring formed on a butterfly wing. Exp Fluids 2013; 54: 1–12.

31.

Lankford

Mayo

Chopra

. Computational investigation of insect-based flapping wings for micro air vehicle applications. J Micro Air Veh 2016; 8: 64–78.

32.

Zhao

Deng

Sane

. Modulation of leading edge vorticity and aerodynamic forces in flexible flapping wings. Bioinspir Biomim 2011; 6: 036007.

33.

Nguyen

Chan

Debiasi

. Experimental investigation of wing flexibility on force generation of a hovering flapping wing micro air vehicle with double wing clap-and-fling effects. J Micro Air Veh 2017; 9: 187–197.

34.

Cros

Llamas

Hernandez

. Vortical patterns generated by flapping foils of variable ratio chord-to-thickness. Exp Fluids 2018; 59: 1–9.

35.

Wang

Zhang

. Lift enhancement on spanwise oscillating flat-plates in low-Reynolds-number flows. Phys Fluids 2015; 27: 061901.

36.

Eldredge

Jones

. Leading-edge vortices: mechanics and modeling. Annu Rev Fluid Mech 2019; 51: 75–104.

37.

Sun

Tang

. Unsteady aerodynamic force generation by a model fruit fly wing in flapping motion. J Exp Biol 2002; 205: 55–70.

38.

Vogel

. Life in Moving Fluids: The Physical Biology of Flow-Revised and Expanded Second Edition. Princeton: Princeton University Press, 2020.

39.

Liu

Ellington

Kawachi

, et al. A computational fluid dynamic study of hawkmoth hovering. J Exp Biol 1998; 201: 461–477.

40.

Luo

Yan

, et al. Autonomous detection of damage to multiple steel surfaces from 360 panoramas using deep neural networks. Comput-Aided Civ Inf 2021; 36: 1585–1599.

An experimental study of the unsteady vortex structures of a clapping-wing micro air vehicle

Abstract

Keywords

Introduction

Experimental methodology

Wind tunnel and test model

PIV experimental setup

Results and discussions

Instantaneous aerodynamic force measurements

Average aerodynamic force measurements

Flow visualization

Method verification and accuracy

Parameter study: effect of some varying parameters on the LEV

Parameter study: effect of some varying parameters on the TEV

High-lift and high-thrust mechanisms

Conclusions

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

References