wake of tandem cylinders

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drag. Hoerner reviewed many of theories developed for LAR wings of non-delta

platforms.

The most important consequence of work at low Reynolds numbers is increasing

in drag, but lift coefficient will be constant approximately and this leads todecreasing lift to drag. In research which Kunz and Kroo [3] have performed at

low Reynolds numbers, they studied NACA0002 to NACA0008 and showed that

for Reynolds number 2000 drag coefficient is much more than Reynolds number

6000 but the lift coefficient is about the same order. Generally, drag growth is

proportional to thickness increase and it will increase as Reynolds number

decreases, but rate of increasing in drag related to zero-thickness drag are

similar in both Reynolds number.

Also, the addition of 2% camber results in a 2.0-2.5 deg shift in the zero lift

angle of attack. It means that cambered airfoil at zero angle of attack has a lift

equal to the lift of the airfoil without camber at 2 to 2.5deg angle of attack [3].

Mueller and Torres have studied Zimmerman wing models and rectangular

wing at tree aspect ratios as 0.5, 1 and 2 experimentally. They showed that

increasing in lift coefficient will continue even after 30 deg of angle of attack

for 0.5 and 1 aspect ratios, but for aspect ratio of 2, after 12 deg angle of attack

it will be halted [4].

Furthermore, according to the extensive application of turbulent boundary

layer, knowing the physics of boundary layer and analyzing turbulence

parameters is important. A turbulence study in the wake of a model wind

turbine placed in a boundary layer developed over rough and smooth surfaces

were performed using hot-wire anemometry, by Chamorro and Porte-Angel[5].

This study showed that the effect of turbine on the velocity defect and added

turbulence intensity is not negligible even in the very far wake, at a distance of

fifteen times the rotor diameter.

Hot-wire anemometry data are much reliable that have been used to validate a

Particle Image Velocimetry (PIV) work by Foucaut, et al [6]in order to study

unsteady characteristics of near-wall turbulent boundary layer. Their aim was

building dynamic boundary conditions near a solid wall,

Farsimadan and Mokhtarzadeh [7] performed an experimental investigation on

flow over NACA 0012 airfoil placed at upstream of a 90 bend. They focused on

in order to reduce the

large eddy simulation spatial resolution that is necessary in this region.


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upper surface boundary layer and downstream vorticities and studied mean

velocity and stream wise turbulent intensity taken in the span wise direction.

In the present work, boundary layer has been studied experimentally and effects

of free stream velocity, angle of attack and also distances between two wing'shave been shown on the main wing's boundary layer. Also, Artificial Neural

Networks have been applied to estimate some values in boundary layer.

1.1. Introduction to Turbulence parameters

To study of a turbulent boundary layer, one needs to analyze some turbulence

parameters such as mean velocity and turbulence intensity [8]. Mean velocity

shows the time averaged velocity and is related to velocity u(t) and velocity

fluctuations u'

(t) as u(t)=Umean + u'

Which N is the number of velocity samples. Standard deviation of flow velocity

determines the turbulence intensity and is known as root-mean-squared

velocity:

(t). Mean velocity can be obtained asequation 1:

=1

()

1

(1)

= ( 11 (() )21

)0.5 (2)

Using velocity standard deviation, we can calculate turbulence intensity as

equation 3:

= 100 (3)There are two other important parameters which are used to study fluids flow

qualitatively; Skewness and Kurtosis. Skewness is a measure of symmetry, or

more precisely, the lack of symmetry of distribution function. Here, skewness

shows the symmetry of velocity related to flow mean velocity. When skewness is

not zero, data is not symmetry related to mean velocity and it cannot be

modeled by a normal distribution. Kurtosis is a measure of whether the data are

peaked or flat relative to a normal distribution. That is, data sets with high

kurtosis tend to have a distinct peak near the mean, decline rather rapidly, and

have heavy tails. Data sets with low kurtosis tend to have a flat top near the


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mean rather than a sharp peak. Skewness and kurtosis are shown in equations 4

and 5 respectively.

= 1

(())3

3

1 (4)

= 1 (())44

1 (5)

2.Experiment details

2.1. Wing model

A two-wing MAV, based on our studies whose wings are reverse Zimmerman

and rectangular have been tested. The main wing's area and chord are about 83

cm2and 10 cm respectively. The aspect ratio is 1 and GOE 723 has been used

for its root airfoil (figure 1). Also, the upper wing which has horizontal

stabilizer role has about 42 cm2

First, boundary layer has been studied for single main wing at three different

free stream velocities and three different angles of attack. The main wing and

stations in which boundary layer has been measured through them are shown in

figure 2 schematically. Free stream velocities are 10, 15 and 20 m/s and anglesof attack are 0, 2 and 4 degrees.

area, and GOE344 has been used for its root

airfoil.

Then, effects of existence of upper wing have been studied on main wing's

boundary layer. There are three positions for the upper wing in which distances

between main wing's trailing edge and upper wing's trailing edge is 3.5, 3 and

2.5 cm that called up1, up2 and up3 respectively.


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Figure1. The wing which is used in present work

2.2. wind Tunnel

Measurements were conducted in a low-speed, open-circuit wind tunnel located

at the Sabzevar Tarbiat Moalem University. Tunnel has a maximum speed of 30

m/s. Over the speed range used for experiments, the turbulence intensity in the

test section has been determined to be approximately 0.1%.

Figure 2. Schematic of the root airfoil and the stations


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A 1.7-m-long test section with a rectangular cross-sectional area of 0.40.4 m

is located downstream of the inlet. Downstream of the test section is a diffuser

that slows the flow. Figure 3 shows a schematic of the wind tunnel.

Figure 3. Schematic of the low-speed wind tunnel in the present work

2.3. measurments

Parameters measured by the flow of hot tungsten 1-D wire anemometer with

diameter 5 m, length of 1.25mm in a constant temperature circuit. The

frequency of the probe calibrated is 5 KHz. Figure 4 shows a schematic of the

1-D hot wire anemometer.

Figure 4. Schematic of the 1-D hot wire anemometer

2.4. Data Acquisition

All experiments data were acquired using a PC-based data acquisition system

performed by FARA SANJESH SABA using the LABVIEW graphical

programming language. An analog/digital (A/D) card was used.

2.5. Neural Network


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ANNs are formed by input data vectors, neurons and output functions. Input

data to the neuron are transformed by means of a base function and leave by an

activation function. Each connection between input and output data and

neurons is made by weight factors.

Each Neural Network applied in this work is solved with three Neurons, basedon a feed forward calculation and using Marquardt non-linear fitting method

[9].

3.Results and Discussion

3.1. Experiments results

Figure 5 shows the effects of different free stream velocities on wing's boundary

layer at zero degree angle of attack. In this figure, velocity profiles for 10 m/s

free stream velocity are shown by symbol + and also they are shown for 15 and

20 m/s by symbols and respectively. As free stream velocity increases,

separation point shifts toward the trailing edge and also boundary layer

thickness decreases. For 10 m/s velocity, the boundary layer thickness reaches

up to 10 mm at the trailing edge of the wing; but for two other velocities, it

seems that results are near to each other and far different from 10 m/s velocity

results.

It is important to say that because of single 1-D hot-wire anemometer, reverse

flows cannot be measured and so velocity profiles from x/c=0.65 to x/c=0.95

are much different from the actual ones. Separation has been occurred and flowis reverse at these stations.

Turbulence intensity for 7 stations in wing's boundary layer is shown in figure

6. As it is mentioned in figure 5, boundary layer thickness is much thicker for 10

m/s free stream velocity. According to the figure 6, there is one maximum peak

for turbulence intensity in each station which is in mean velocity gradient area.

Maximum turbulence intensity is greater for 15 m/s velocity than other two

velocities and it shifts upward as x/c increases. Also, when free stream velocity

is 15 m/s, the range of turbulence area is greater than the other velocities.


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Furthermore, maximum turbulence intensity in the first and second stations (i.e.

x/c=0.45 and x/c=0.55)is greater for 20 m/s velocity than 15 m/s velocity; it

seems that when separation is not occurred, turbulence intensity in the

boundary layer increases as free stream velocity increases.

Figures 7 and 8 show the effects of angle of attack on wing's boundary layer at

10 m/s free stream velocity. In these figures, profiles for zero degree angle of

attack are shown by symbol + and also they are shown for 2 and 4 degrees by

symbols and respectively. Figure 7 shows that increasing in angle of attack

increases probability of separation and shifts the separation point toward the

leading edge. Also, increasing in angle of attack increases the boundary layer

thickness.

According to the figure 8 which shows the turbulence intensity in wing's

boundary layer, increasing in angle of attack increases turbulence intensity and

distance from wing's surface to maximum peak of turbulence intensity.

Effects of upper wing on main wing's boundary layer have been studied in

figures 9 and 10 at zero angle of attack and 10 m/s free stream velocity. In these

work, there were three positions for the upper wing which are shown in these

figures. When distance between trailing edge of upper wing and that of main

wing is 3.5 cm, it is called up1 and shown by symbol. Also, this distance is 3and 2.5 for up2 and up3 and is shown by symbols and respectively.

Considering the figure 9, existence of upper wing leads to decreasing in

boundary layer thickness; furthermore decreasing in distance between two

wings amplifies this. From figure 9 we can conclude that existence of the upper

wing will delay separation and shifts the separation point toward the trailing

edge.

Figure 10 shows the effects of upper wing on main wing's boundary layerturbulence intensity. According to this figure, existence of the upper wing

decreases turbulence intensity so much; and as distance between two wings

decreases both turbulence intensity peak and area will decreases. Hence, in up3

when distance between two wings is 2.5, turbulence intensity in the main wing's

boundary layer is minimum.


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Figure 5- boundary layer velocity profiles at zero degree angle of attack

Figure 6- boundary layer turbulence intensity profiles at zero degree angle of attack

0.50

0.00 1.00

2.00

6.00

10.00

14.00

0.00

4.00

8.00

12.00

Y(mm)

0.50

0.00 1.000.50

0.00 1.000.50

0.00 1.00

U/Uref

x/c=0.45 x/c=0.55

x/c=0.65

x/c=0.75

Boundary layer profiles at 0deg angle

10 m/s

15 m/s

20 m/s

0.50

0.00 1.00

x/c=0.85

0.00 1.00 0.00 1.00

x/c=0.9

x/c=0.95

1.00 3.00

0.00 2.00

Tu

2.00

6.00

10.00

14.00

0.00

4.00

8.00

12.00

Y(mm)

1.00 3.00

0.00 2.00 4.00

Tu

2.50 7.50

0.00 5.00 10.00

Tu

2.50 7.50

0.00 5.00 10.00

Tu

x/c=0.45

x/c=0.55

x/c=0.65

x/c=0.75

Turbulence intensity in boundary layer at 0deg angle of attack

10 m/s

15 m/s

20 m/s

5.00 15.00

0.00 10.00

Tu

x/c=0.85

0.00 10.00 20.00

Tu0.00 10.00 20.00

Tu

x/c=0.9

x/c=0.95


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Figure 7- boundary layer velocity profiles at 10 m/s free stream velocity

Figure 8- boundary layer turbulence intensity profiles at 10 m/s free stream velocity

0.50

0.00 1.00

2.00

6.00

10.00

14.00

0.00

4.00

8.00

12.00

Y(mm)

0.50

0.00 1.000.50

0.00 1.000.50

0.00 1.00

U/Uref

x/c=0.45 x/c=0.55

x/c=0.65

x/c=0.75

Boundary layer profiles at 10m/s velocity

0 deg

2 deg

4 deg

0.50

0.00 1.00

x/c=0.85

0.00 1.00

x/c=0.95

0.50 1.50

0.00 1.00 2.00

Tu

2.00

6.00

10.00

14.00

0.00

4.00

8.00

12.00

Y(mm)

1.00 3.00

0.00 2.00

Tu

2.00 6.00

0.00 4.00

Tu

2.00 6.00

0.00 4.00

Tu

x/c=0.45x/c=0.55

x/c=0.65x/c=0.75

Turbulence Intensity in Boundary layer at 10m/s velocity

0 deg

2 deg

4 deg

5.00 15.00

0.00 10.00

Tu

x/c=0.85

0.00 10.00 20.00

Tu

x/c=0.95


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Figure 9- boundary layer velocity profiles at 10 m/s free stream velocity and zero

degree angle of attack and effects of upper wing

Figure 10- boundary layer turbulence intensity profiles at 10 m/s free stream velocity

and zero degree angle of attack and effects of upper wing

0.50

0.00 1.00

2.50

7.50

12.50

0.00

5.00

10.00

15.00

Y(mm)

0.50

0.00 1.00

U/Uref

0.50

0.00 1.00

x/c=0.85 x/c=0.95x/c=0.9

Boundary layer profiles at 0deg and 10 m/s

Single wing

Up1

Up2

Up3

2.50 7.50

0.00 5.00 10.00

5.00

15.00

0.00

10.00

20.00

Y(m

m)

5.00 15.00

0.00 10.00

Tu

5.00 15.000.00 10.00 20.00

x/c=0.85

x/c=0.95x/c=0.9

Turbulence Intensity at 0deg and 10 m/s

Single wing

Up1

Up2

Up3


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3.2. Artificial Neural Network

First, an artificial Neural Network is trained to determine turbulence

parameters in x/c=0.9 for 10 m/s free stream velocity, zero degree angle of

attack and up3. We picked up3 because the minimum turbulence intensity wascaptured in the boundary layer; hence that is the best location for upper wing

from turbulence intensity point of view. As it shows in table 1, Hot-wire results

and Neural Network results for a point (y=4.2 mm) are compared. Now using

this network, turbulence intensities for mid-points for x/c=0.9 at 10 m/s velocity

and zero degree angle of attack is shown in figure 11.

Table1. Comparison between hot-wire and Neural Network results for one wing's boundary

layer point (y=4.2 mm, x/c=0.9 at 10 m/s free stream velocity, up3)

Results Tu Skewness Kurtosis Urms

Hot wire 4.09106 -0.00551 0.0873 0.409106

Neural

Network

4.0908 -0.0060 0.0874 0.40908

Error 0.006% 9% 0.11% 0.006%

As mentioned in figure 6, turbulence intensities in main wing's boundary layer

at zero degree angle of attack and 10 m/s free stream velocity has been studied.Maximum turbulence intensity measured using Hot-wire anemometer, in each

station (x/c) is shown in table 2. For other points through the wing's chord (x/c),

turbulence intensities are estimated and shown in figure 12.


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Figure 11- Turbulence intensity at x/c=0.9 and up3, Hot-wire results and Neural Network

estimated values

Table2. Hot-wire results for maximum turbulence intensities in single wing's boundarylayerat 10m/s free stream velocity and zero degree angle of attack

x/c 0.55 0.65 0.75 0.85 0.9 0.95

Max. Tu 2.23312 4.58271 6.13497 8.07906 9.39714 19.08466

0 1 2 3 4 5 6 7 8 9 100

1

2

3

4

5

6

Y(mm)

Tu

HoT-wire

NeuralNeTwork


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Figure 12- Maximum turbulence intensities single wing's boundarylayer at 10m/s freestream velocity and zero degree angle of attack, Hot-wire results and Neural Network

estimated values

4. Conclusion

In the present work, effects of free stream velocity and angle of attack have been

studied on a single wing's boundary layer. Boundary layer thickness increases

as free stream velocity decreases and angle of attack increases. Also,

separation point shifts toward the trailing edge as free stream velocity increases

or angle of attack decreases. Furthermore, existence of the upper wing

decreases both boundary layer thickness and turbulence intensity; for up3,

which distance between two wings is 2.5 cm, turbulence intensity is minimum.

Moreover, Artificial Neural Networks have been applied to estimate maximum

turbulence intensities in the single wing's boundary layer and mid-points for

turbulence intensity profile of up3.

5.Acknowledgments

Authors appreciate SABZEVAR TARBIYAT MOALLEM UNIVERSITY for

cooperation. Also, we are thankful of the editor and reviewers of the

'Experimental Thermal and Fluid Science' journal for their time and

cooperation.

0.4 0.5 0.6 0.7 0.8 0.9 10

5

10

15

20

25

30

35

x/c

max.Tu

HoT-wire

NeuralNeTwork

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