numerical study on aerofoil stall - :: welcome to ijerest :: · · 2015-05-11this aerofoil has...

International Journal of Emerging Researches in Engineering Science and Technology-

Vol-2-Issue-4-April-2015-ISSN: 2393-9184

27

Abstract—This work involves usage of Reynolds Averaged

Navier Stokes Equation (RANSE) based Computational Fluid

Dynamics (CFD) approach for the determination of stall angle

for Wortmann FX 79-W-151 aerofoil. Geometrical modelling of

this aerofoil has been done using ANSYS ICEM CFD and

simulations have been carried out using ANSYS CFX. Pitch

motion which is a rotation about y-axis and occurring in x-z

plane has been depicted here as yaw motion i.e. rotation about z

axis in x-y plane so that the flow around the aerofoil section can

be studied during rotation.Simulation of flow has been

accomplished for various angles of attack for determining both

static and dynamic stall. The limitation of RANSE solver with the

angle of attack and the subsequent flow separation has also been

studied.

Index Terms—Aerodynamics,CFD,Dynamic stall,Static stall.

I. INTRODUCTION

OMPUTATIONAL FLUID DYNAMICS (CFD) involves

solving of fluid flow problems by numerically solving the

Navier-Stokes equations. Navier-stokes equations are of

prime importance as they help solve majority of fluid flow

problems as its simplification leads us to Euler’s equation, Potential equations and Linearized potential equations. CFD

helps in easier identification of flaws in the design and

accurately predicts the fluid and thermal flows, thereby saving

considerable time and cost in the production process. Thus

CFD finds its application in various fields such as aerospace,

marine, medical, automotive and chemical industries.

In the present work, aerodynamic study of a flow around an

aerofoil has been studied. Stall is an unfavorable condition

that exists when the lift on the aerofoil decreases on increase

in the angle of attack. This situation is highly undesirable as

the aircraft will start spinning downwards losing its altitude.

On reviewing various literatures, it can be understood that a

quite a number of wind tunnel experiments have been done in

estimating static and dynamic stall. Numerical studies using

panel methods and Reynolds Averaged Navier Stokes

Equation (RANSE) based CFD have been limited only to the

Manuscript submitted for review on 20 January 2015.This work was

supported by the Department of Mechanical engineering, SSET, Ernakulam,

India.

Praphul T, B.Tech, Mechanical engineering, SSET, Ernakulam, India. (e-

mail: [email protected]).

Dr. Sheeja Janardhanan,Associate Professor, Department of Mechanical

Engineering, SSET, Ernakulam, India. (e-

mail:[email protected]).

estimation of static stall. Thus the idea of this work is mooted

based on [2]. This work deals with the measurements with

sinusoidal pitching and constant angular velocities and

dynamic stall characteristics. Under dynamic stall conditions,

maximum value of lift coefficient was up to 80% higher than

that for static lift. In the present work, pitch (rotation about y-

axis) motions in x-z plane have been transformed to the x-y

plane and consequent yaw (rotation about z-axis) motions

have been targeted to find out stall angles in static and

dynamic motions of the aerofoil.

II. PROBLEM FORMULATION

A. Geometrical modelling

Geometrical modelling of the aerofoil has been carried out

using ICEM CFD. Data points were imported to ICEM CFD

using a .dat file obtained from UIUC airfoil coordinates

database. The aerofoil was then modelled to the specifications

as obtained from [2]. Fig. 1shows the aerofoil geometry.

To simulate the wind tunnel experiment [2], a wind tunnel of

dimensions 9m x 2.5mx 2m has been created around the

aerofoil using ICEM CFD.

Numerical Study on Aerofoil Stall

Praphul Tand Sheeja Janardhanan

C

Fig. 1Aerofoil geometry

Fig. 2.Wireframe model of the wind tunnel



28

The inner domain and outer domain has been created using

ICEM CFD to perform both the static and dynamic stall

simulations on the aerofoil are as follows

B. Meshing

Structured H mesh has been chosen for the analysis. Grid

independency study has been carried out using ANSYS CFX.

Mesh size with density of 1.5 million cellshas been thus

chosen as the adequate mesh size.For performing the analysis

of static and dynamic stall, the same mesh density as obtained

through grid independency was retained. Meshing strategy

involved for carrying out the static and dynamic stall

simulations has been based on [6]where an interface mesh

with circular cylindrical inner domain encompassing a ship

and cuboidal fluid domain were developed and used for

hydrodynamic analysis. This type of mesh reduces the

complexity of rotating the aerofoil and remeshing each time

for an orientation, facilitating the rotation of cells in the inner

domain alone, thus saving considerable time and effort.

C. Boundary conditions

Simulations carried out for wind tunnel experiment and stall

(both static and dynamic) involved the following boundary

conditions.

The boundary conditions are as follows:

Aerofoil – wall – no slip wall

Bottom – wall – no slip wall

Inlet – inlet

Outlet – outlet

Side 1 – wall – no slip wall

Side 2 – wall – no slip wall

Top – Opening

Turbulent intensity was kept below 1%, air flow speed was

taken to be 50 m/s as in [2].

The turbulence model has been taken ask-ω SST as found

from [1].

Fig. 3. Wireframe model of the inner domain.

Fig. 4. Wireframe model of the outer domain.

Fig. 5. Mesh model selected after performing the grid independency

study.

Fig. 6. Mesh model of the inner domain.

Fig. 7. Mesh model of the outer domain.

Fig. 8. Boundary condition as applied to the aerofoil



29

D. CFD analysis

1) Static stall

Static stall is the stall condition observed for the flow over the

aerofoil at a fixed angle of attack. For static stall estimations,

the inner domain was rotated about the z axis in counter

clockwise as well as clockwise directions for various angles of attack. The various angles of attack under consideration here

are from 0 degree to 15 degree in steps of 2.5 degree

increments for each angle.

2) Dynamic stall

Dynamic stall occurs when there is sudden change in the angle

of attack by the aerofoil. A sinusoidal rotation about z-axis

was given to the inner domain in CFX pre in order to obtain

yaw movement. The sinusoidal function is as follows:

ta sin (1)

= Amplitude of oscillation.

a=Maximum amplitude of oscillation = 0.2618 rad

= Angular frequency of oscillation = 0.5 rad/sec

t = instantaneous time in s

.txt, .xlsx files were written to give inputs to the CFX solver

for interpolating the values. Animation on the dynamic stall

analysis was also performed.

III. RESULTS

A. CFD Validation

Validation of CFD was done by comparing the values of

coefficient of lift obtained for the aerofoil at zero degree of attack between the CFX simulation and the experimental value

obtained from [2]as shown

The values thus are close to each other thus validating the mesh and CFD analysis.

B. Static stall

1) Anticlockwise direction

It is observed that the stall occurs between 12.5 and 15

degrees. This is because of the flow separation that occurs

between 12.5 and 15 degrees that causes the lift force to drop

causing stall.

Fig. 9. Boundary condition as applied to the wind tunnel

Fig. 10. Graph plot comparing values of coefficient of lift vs. angle of

attack for static stall simulations performed in anticlockwise direction.

0, 0.216

2.5, 0.414

5, 0.571

7.5, 0.728

10, 0.92

12.5, 0.95

13.75, 0.896

15, 0.937

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2.5 5 7.5 10 12.5 13.75 15

Co

effi

cien

t o

f li

ft (

Cl)

Angle of attack (degrees)

Static Stall in Yaw (Anticlockwise Direction)

TABLE I

COMPARISON OF COEFFICIENT OF LIFT

Experiment (Mohlmann,

2007)

Present CFD

lC

0.2 0.2144

Fig. 11. Velocity and pressure plots on the aerofoil at 0 degree angle of

attack.



30


attack in the anti-clockwise direction.

Fig. 14. Velocity and pressure plots on the aerofoil at 7.5 degree angle

of attack in the anti-clockwise direction.


of attack in the anticlockwise direction


attack in the anti-clockwise direction.



31

2) Clockwise direction

In case of clockwise rotation, there is no stall even at 15

degree even though there is evident flow separation at the

lower part of the aerofoil. Stall may occur at higher angles but

due to the limitation of the present RANSE solver (CFX),

simulations for angles of attack greater than 15 degree could

not be carried out.

Simulations for angles greater than 15 degree may be carried

with much more powerful CFD solver such as Large Eddy

Simulations (LES) which requires a computational

environment with much higher requirements and lower eddies

will be filtered out. This is however beyond the scope of

present work.

Fig. 18. Velocity and pressure plots on the aerofoil at 15 degree angle of attack in the anti-clockwise direction.


of attack in the anti-clockwise direction.

Fig. 17. Velocity and pressure plots on the aerofoil at 13.75 degree

angle of attack in the anti-clockwise direction.

Fig. 19. Graph plot comparing values of coefficient of lift vs. angle of

attack for static stall simulations performed in clockwise direction

0, 0.216

-2.5, 0.0483

-5, -0.1114

-7.5, -0.2356

-10, -0.2866

-12.5, -0.3086

-13.75, -0.3185

-15, -0.33175

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0 -2.5 -5 -7.5 -10 -12.5 -13.75 -15

Co

effi

cien

t o

f li

ft (

Cl)

Angle of attack (degrees)

Static Stall in Yaw (Clockwise Direction)



32


attack.



33

C. Dynamic stall

In the simulations for dynamic stall, lift, drag and moment on


attack in the clockwise direction.

Fig. 22. Velocity and pressure plots on the aerofoil at 5 degree angle of attack in the clockwise direction.

Fig. 21. Velocity and pressure plots on the aerofoil at 2.5 degree angle of attack in the clockwise direction.


of attack in the clockwise direction.


attack in the clockwise direction.


of attack in the clockwise direction.

Fig. 26. Velocity and pressure plots on the aerofoil at 13.75 degree

angle of attack in the clockwise direction.



34

the aerofoil was monitored. The aerofoil was rotated in the

clock wise direction first and then into anticlockwise direction.

In the simulation performed it was observed that the solver

was able to achieve clockwise rotation of the aerofoil for half

a cycle. It was able to achieve maximum amplitude

corresponding to 15 degree in the clockwise rotation of the

aerofoil. The post processed results happening at each quarter

of the cycle are as shown from Fig. 29-31. It shows that flow separation occurs at the quarter cycle i.e. at T=3.33 sec that

corresponds to 15 degrees clockwise rotation. But the flow

separation is at the lower portion of the aerofoil which is not

of much importance compared to that at the upper portion of

the aerofoil. Stall occurs only at the upper portion of the

aerofoil that will be justified by the fall in magnitude of the lift

force and the flow separation at the upper surface.

Max lift force at -15 degree (dynamic) = -171 N

Max lift force at -15 degree (static) = -101 N

The percentage increase of lift force in dynamic stall conditions is:

%33.69100101

101171

It was observed that after completing the clockwise rotation, i.e. when the aerofoil started rotating in the anticlockwise

rotation, the solver was able to rotate the aerofoil only to an

angle of maximum 6 degrees. The post processed results at

3/4th quarter corresponding to maximum displacement of 6

degrees is as shown in Fig. 33. The reason for this

phenomenon is due to the computational limitation of the

solver as a result of excessive turbulence and flow separation.

The periodicity in vortex shedding is also evident from the trends of forces and moments from 7 sec onwards from Fig.

28-30.

Fig. 32. Velocity contour plot of dynamic stall simulation

corresponding to 0.5 Time period = 6.66sec.

Fig. 28. Lift force vs. Time Graph

Fig. 29. Drag force vs. Time Graph

Fig. 30. Moment vs. Time Graph





35

D. Limitation of RANSE Solver

It has been one of the objective of this work to find out the

limitation of RANSE solver. RANSE solver used here is

ANSYS CFX. It has been found out that the RANSE solver is

susceptible to various numerical errors as found out as

follows:

The solver faced problems in converging solutions at higher

degree angle of attack and in higher degrees of turbulence.

During static stall estimations, the solver was unable to

converge solutions at angle of attack greater than 15 degree

both in the clockwise and anticlockwise directions.

During dynamic stall simulations, the solver was unable to

rotate the aerofoil for angle of attack greater than 6 degree.

These limitations can be avoided by using a much powerful solver such as Large Eddy Simulation (LES) solver distributed

by OPENFOAM foundation. This requires much higher

computer system requirements which was one of the limitation

of the work which justifies the usage of CFX as the solver

used in the present simulations.

IV. CONCLUSIONS

The work here presents a method for estimating

aerodynamic stall using RANSE based CFD as well as

exploring its efficacies and limitations. Following conclusions

can be drawn from the work carried out:

RANSE based CFD provides a simplified platform to

understand flow and associated phenomenon around aerofoil

bodies which necessitates the use of an optimum grid and

meshing strategy.

RANSE can capture flow separation, turbulence and eddies

only to a certain extent. Here 15 degrees is found to be the

limit beyond which numerical errors and instabilities creep in.

The stall angles falling in this limit and well captured by the

solver in static simulations.

Due to asymmetry of the aerofoil static simulations in

clockwise and anticlockwise directions differ considerably.

Clockwise rotations result in stall much beyond 15 degrees

which could not be captured by the present solver. On the

other hand anti clock-wise rotations resulted in a stall angle of

12.5 deg.

Dynamic stalls are at least 60-80% more than static stall.

Stall is not noticed in clockwise rotation while in

anticlockwise stall occurred much earlier compared to its

static counterpart. The trend shows a very good qualitative

prediction. But due to the limitation of the solver the

simulations had to be stopped much before one complete time

period of simulation.

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[2] Gerrit Wolken-M¨ohlmann, Pascal Knebel, Stephan Barth and Joachim

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Conference Series.

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[4] Nicholas D. Liggett, “Numerical investigation of static and dynamic

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0118-4



http://www.academicjournals.org/JMER

http://iopscience.iop.org/1742-6596/75/1/012026

http://iopscience.iop.org/1742-6596/75/1/012026

http://www.sciencedirect.com/science/article/pii/S0894177704001141

http://www.ijert.org/

http://link.springer.com/article/10.1007/s12206-011-0118-4

http://link.springer.com/article/10.1007/s12206-011-0118-4

numerical study on aerofoil stall - :: welcome to ijerest :: · · 2015-05-11this aerofoil has...

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