CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model

CFD Analysis and Wind Tunnel Experiment on a

Typical Launch Vehicle Model

Selvi Rajan. S1*, Santhoshkumar. M2, Lakshmanan. N3,

Nadaraja Pillai. S4 and Paramasivam. M5

1Scientist, Structural Engineering Research Centre, CSIR Campus,

Taramani, Chennai – 600 113, Tamil Nadu, India2Structural Engineer, Vibromech Engineers & Services ltd.,

Chennai, Tamil Nadu, India3Director, Structural Engineering Research Centre, CSIR Campus,

Taramani, Chennai – 600 113, Tamil Nadu, India4PhD Research Scholar, Wind Engineering Research Centre, Tokyo Polytechnic University,

Japan 243-02975PDF Research Scholar, Wind Engineering Research Centre, Tokyo Polytechnic University,

Japan 243-0297

Abstract

In order to understand the physical phenomena of the wind flow over the typical launch vehicle,

the flow was simulated using both Wind tunnel and Computational Fluid Dynamics (CFD). In the

present study, tests were conducted on a 1:50 scaled model of a launch vehicle. The model was

subjected to two wind conditions, wind flow normal to the shorter plan dimension � = 0�, where the

three main cylinders of the model were one behind the other and wind flow normal to the longer plan

dimension, � = 90�, where all the three main cylinders of the vehicle are subjected to direct wind

pressure in the windward direction. Based on the CFD studies, the flow pattern and the force

coefficients were derived. To validate these results, wind tunnel tests were carried out on a 1:50 scaled

rigid and light-weight models respectively, for obtaining path lines and force coefficients. Results on

streamlines obtained based on CFD simulation and wind tunnel experiments compared very well. The

force coefficients in both directions were evaluated from CFD results showed good agreement with the

corresponding measured values based on wind tunnel experiment.

Key Words: CFD Simulation, Boundary Layer Wind Tunnel, Launch Vehicle, Flow Visualization

1. Introduction

There are many simulation methods and different

models are available to access the application of CFD

[1,2] in the field of aerodynamics and wind Engineering.

Murakami et al. [1,3] show such a simulation over the

surface mounted cubic model with the k-� and LES mo-

dels. Many studies show that the critical shapes can have

significant unsteady effects. Different shapes can cause

sudden changes in the size and structure of the wake and

corresponding large changes in drag. In current competi-

tive environment there is a need to design the satellite

launch vehicles which will be capable of launching even

under some unforeseen changes in the atmospheric con-

ditions. One such situation was aroused when PSLV-C5

launched at the time of heavy rain from Sriharikota, In-

dia in Oct. 2003 [4]. There is always a possibility of

storms, cyclones and tornados near the launching station

during the designed period of launch. Before launching,

the Mobile Service Tower (MST) is taken away from the

launch pad. The Umbilical tower that is fully exposed to

atmospheric wind supports the launch vehicle. It be-

Tamkang Journal of Science and Engineering, Vol. 12, No. 3, pp. 223�229 (2009) 223

*Corresponding author. E-mail: [email protected]

comes necessary to test the launch vehicles to atmo-

spheric wind loads under simulated Atmospheric Boun-

dary Layer (ABL) flow. Although sufficient studies on

the flow over some critical bodies are available, there are

not many studies on the physical phenomena of flow

around a launch vehicle for the problem of wind in hori-

zontal direction. Airflow around the launch vehicle mo-

del is complicated since the Boosters, Strapons are clo-

sely packed with main stage. The cross-section looks like

compound.

Atypical launch vehicle model of scale 1:50 as shown

in Figure 1, was considered for the present study. Prior to

wind tunnel testing a detailed understanding on the flow

behaviour around the launch vehicle was thought to be

essential for proper instrumentation and collection of

data. There was no sufficient literature available for flow

over compound cylinder like structures. In order to have

some preliminary ideas about the flow behaviour, a CFD

analysis was done as a pre-experimental study using test

section inlet conditions. Through flow visualisation, flow

aspects relating to points of separation, re-attachment

and wake flow can be studied besides knowing how the

air moves around an object and/or what forces it exerts

on the object. Flow visualisation techniques on models

in the low speed wind tunnel are mostly based on smoke,

powders and tufts. Force data may be taken simulta-

neously with each of these flow visualisation techniques

[5]. Weinstein [6] used flow visualisation technique to

examine rocket sled flow fields and to obtain the aerody-

namic flow field around aircraft in flight. Kompenhans

et al. [7] have used Particle image velocimetry (PIV) to

record the complete flow velocity field in a plane of the

flow to obtain information about unsteady flow fields.

Based on the literature [5], dry ice with hot water based

mixture was tried initially to visualise the flow pattern. It

was observed that when dry ice came in contact with hot

water, the generated smoke was dense and it settled to

the floor of the wind tunnel instead of getting transported

by the flow. Subsequently, a mixture of glycerin and dis-

tilled water had been tried as the source material. The

main advantage of the CFD predictions and its validation

using wind tunnel experiments are discussed in this paper.

2. Numerical Simulations

The computational domain is shown in Figure 2.

There are possibilities for the wind to approach from all

the four directions. Since the model is symmetric, the

computations were done only for two cases. Case_1:

Wind approaching from west direction, i.e., wind flow

normal to the shorter plan dimension � = 0�, where the

three main cylinders are one behind the other. Case_2:

Wind approaching from south direction, i.e., wind flow

normal to the longer plan dimension, � = 90�, where all

the three main cylinders are subjected to direct wind pres-

sure in the windward direction. The computational do-

main was meshed with special meshing feature called

“embedded grids” to increase the cell density near the

model cross-section. Figure 3 shows embedded mesh re-

224 Selvi Rajan. S et al.

Figure 2. Computational domain.Figure 1. Typical launch vehicle model.

gion near the model. There were about 32,000 hexahe-

dral cells in the each computation domain. The numeri-

cal analysis used mass and momentum conservation equ-

ations in two dimensions for steady state, incompressible

flow. A third order QUICK scheme used for modeling

the convective terms of the momentum equations. For

the present study a k-� turbulence model with logarith-

mic turbulent wall functions available in commercial

CFD package STAR-CD was employed [8]. It contains a

full description of the equations in the code, its numeri-

cal methodology and capabilities. The k-� turbulence

model available in STAR-CD was validated by many au-

thors [8]. Mean velocity and pressure distributions were

further obtained based on the CFD computation.

3. Wind Tunnel Test

To validate CFD results, a single component load

cell was designed and fabricated to obtain force coeffi-

cients in two orthogonal directions. The launch vehicle

model was fabricated to a geometric scale of 1:50 with

great care to accurately model the cross-section. The

light-weight (hollow) model made of wood as shown in

Figure 4 was positioned suitably on the load cell within

the test section of the tunnel. Load cell was then cali-

brated by applying static loads in both x and y directions

and the corresponding calibration factors are shown in

Figure 5. The model was subjected to various wind speeds

of 2.6, 6.9, 7.4, and 10.3 m/s, with the directions of flow

CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model 225

Figure 3. Embedded (Discontinuous) Mesh near the model.Figure 4. Force model under test in boundary layer wind

tunnel.

Figure 5. Calibration charts corresponding to x and y direction, respectively.

kept normal to the two orthogonal axes of the launch ve-

hicle. Corresponding to each of the directions, mean va-

lues of force coefficients were derived. Reference area,

A = �D2/4 (m2)

where D = effective diameter

Reference dynamic pressure = ½� U2 (Pascals)

where � = density of air, 1.2 kg/m3

and U = mean wind velocity (m/s)

Mean wind force per meter, in each direction = Cf � Vf

where CN is the calibration factor corresponding to the

direction (from Figure 5)

and VN is the output of the strain gauge

Coefficient of force = (Cf � Vf) / [(½� U2) � A] (1)

Similarly, the force coefficient for the other direction

was determined. In addition, a rigid model made of

solid stainless steel was fabricated and positioned in the

downstream side of the test section of the wind tunnel to

investigate the flow behaviour around the model. The

model was subjected to a low wind speed of 1.2 m/s, to

enable to capture the flow images. The flow lines were

visualized using glycerin mixture and were captured us-

ing a CCD camera.

4. Results and Discussions

Pressure data and the force data are expressed in

terms of dimensionless coefficients for the purpose of

comparison. As per Bernoulli’s equation the surface pres-

sure on the body is usually expressed in the form of non-

dimensional pressure coefficient as:

(2)

where, P is the pressure at required point and P0 is the ref-

erence pressure, � is the density of air and U is the free

stream velocity. The pressure coefficients are resolved

and algebraically added to the corresponding direction to

obtain force coefficient. Results on pressure distribution

as obtained from CFD study on the model were further

analysed to obtain force coefficients for both the test

cases of wind flow normal to the shorter plan dimension

0� (case 1) and wind flow normal to the longer plan di-

mension, 90� (case 2) and these values were found to be

0.23 and 1.18. The force coefficients using wind tunnel

were derived based on force measurement and were

computed as 0.25 and 1.2 respectively.

The aim of the present study was to predict the quali-

tative as well as quantitative information on velocity,

pressure, turbulence parameters like turbulence kinetic

energy, turbulence energy dissipation and wake. Figure

6 shows the mean velocity distributions for case 1 and

case 2 respectively. Figures 7 and 8 show the instanta-

neous streamline pattern for both the cases based on CFD

simulation in comparison with flow visualization con-

ducted experimentally on the rigid model of the launch

vehicle using wind tunnel. The results imply that the vor-

tex wake developing behind a group of cylinders is, to

some extent, similar to that of a single bluff body. The

same has been observed by different author [9]. Hence,

the value of force coefficient for case 2, is almost same as

the value of drag coefficient for a single cylinder, namely

1.2. The value of force coefficient in the other direction

was compared with the available literature on similar


Figure 6. Mean velocity distribution for case 1 & case 2.

type of study to further validate the results [10,11]. The

values were respectively reported as 0.38 and 0.30 as

base drag coefficients under subsonic wind, which can

be compared with the value as obtained from the wind

tunnel test as 0.25.

The figures shown below give the clear idea about

free shear and recirculation regions. Also one can realise

the free shear in the corner regions during experimenta-

tion because of the some inadequacies, hence it is quite

tedious to measure the data at more points. However it

shows the sufficient information for the free shear visu-

ally. Flow visualization studies conducted using wind

tunnel, were also shown for comparison in Figures 7 and

8. The wake survey was done for a distance of 10 D be-

hind the model at 12 stations for both the cases. The ve-

locity was non-dimensionalised and is shown in Figure 9

for case 1 and case 2, respectively. The static pressures

were computed over 280 pressure locations over the mo-

del and presented in terms of non-dimensionalised pres-

sure coefficients, Cp in Figure 10. This pressure distribu-

tion provides the critical regions of pressure and helps to

fix up the locations for pressure measurement.

5. Conclusion

CFD simulation was conducted on a 1:50 scaled

model of a rocket launching vehicle for two cases of � =

0� and � = 90�. Based on the CFD studies, the flow pat-

tern and the force coefficients were derived. To validate

these results, wind tunnel tests were carried out using

1:50 scaled rigid and light-weight models respectively,

for obtaining flow lines and force coefficients. Follow-

ing are the conclusions derived:

� The force coefficients for both the test cases of

wind flow normal to the longer plan dimension � =

0� and wind flow normal to the shorter plan dimen-

sion, � = 90� were found to be 0.23 and 1.18. Cor-

responding to each of the directions, the force co-

efficients were derived based on force measure-

ment using wind tunnel and were found to be 0.25


Figure 7. Instantaneous streamlines for case 1.

Figure 8. Instantaneous streamlines for case 2.

and 1.2 respectively. These values were further

compared well with the values available in the li-

terature.

� The predicted flow field around the model was

examined using CFD as well as based on wind

tunnel experiment. There was a very good com-

parison, as can be seen from Figures 7 and 8.

� The CFD predictions provide good aid for fixing

up the measurement points for velocity pressure

measurement in all the directions besides provid-

ing better understanding on the flow pattern.

� Such pre-experimental CFD study helps in reduc-

ing the number of repetitive experiments in the

collection of data besides reducing the cost and

time considerably when compared to the tradi-

tional approach of wind tunnel experiments, for

certain type of typical selected studies. In the case,

where the levels of turbulence intensities are of


Figure 9. Mean velocity defect profiles on wake centerline corresponding to case1 and case2.

Figure 10. Pressure distribution over the model.

high importance, it is imperative to resort to wind

tunnel experiments.

References

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ing the k-� Model by Means of a Wind Tunnel Test and

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[8] STAR-CD version 3.15A manuals, Computational

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[9] David Sumner, “Closely Spaced Circular Cylinders in

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Manuscript Received: Jul. 16, 2008

Accepted: Jun. 10, 2009


CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model

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