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

Transcription

1 Tamkang Journal of Science and Engineering, Vol. 12, No. 3, pp (2009) 223 CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model Selvi Rajan. S 1 *, Santhoshkumar. M 2, Lakshmanan. N 3, Nadaraja Pillai. S 4 and Paramasivam. M 5 1 Scientist, Structural Engineering Research Centre, CSIR Campus, Taramani, Chennai , Tamil Nadu, India 2 Structural Engineer, Vibromech Engineers & Services ltd., Chennai, Tamil Nadu, India 3 Director, Structural Engineering Research Centre, CSIR Campus, Taramani, Chennai , Tamil Nadu, India 4 PhD Research Scholar, Wind Engineering Research Centre, Tokyo Polytechnic University, Japan PDF Research Scholar, Wind Engineering Research Centre, Tokyo Polytechnic University, Japan 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 models. 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 author. sselvi@sercm.org corresponding large changes in drag. In current competitive 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 conditions. One such situation was aroused when PSLV-C5 launched at the time of heavy rain from Sriharikota, India in Oct [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-

2 224 Selvi Rajan. S et al. comes necessary to test the launch vehicles to atmospheric wind loads under simulated Atmospheric Boundary 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 horizontal direction. Airflow around the launch vehicle model is complicated since the Boosters, Strapons are closely 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 simultaneously with each of these flow visualisation techniques [5]. Weinstein [6] used flow visualisation technique to examine rocket sled flow fields and to obtain the aerodynamic 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 distilled 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 pressure in the windward direction. The computational domain 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- Figure 1. Typical launch vehicle model. Figure 2. Computational domain.

3 CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model gion near the model. There were about 32,000 hexahedral cells in the each computation domain. The numerical analysis used mass and momentum conservation equations 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-e turbulence model with logarithmic 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 numerical methodology and capabilities. The k-e turbulence model available in STAR-CD was validated by many authors [8]. Mean velocity and pressure distributions were further obtained based on the CFD computation. 225 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 calibrated 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 3. Wind Tunnel Test To validate CFD results, a single component load cell was designed and fabricated to obtain force coeffi- 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.

4 226 Selvi Rajan. S et al. kept normal to the two orthogonal axes of the launch vehicle. Corresponding to each of the directions, mean values of force coefficients were derived. Reference area, A= D 2 /4 (m 2 ) where D = effective diameter Reference dynamic pressure = ½ U 2 (Pascals) where = density of air, 1.2 kg/m 3 and U = mean wind velocity (m/s) Mean wind force per meter, in each direction = C f V f where C N is the calibration factor corresponding to the direction (from Figure 5) and V N is the output of the strain gauge Coefficient of force = (C f V f )/[(½ U 2 ) 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 using a CCD camera. 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 qualitative 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 instantaneous streamline pattern for both the cases based on CFD simulation in comparison with flow visualization conducted experimentally on the rigid model of the launch vehicle using wind tunnel. The results imply that the vortex 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 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 pressure on the body is usually expressed in the form of nondimensional pressure coefficient as: (2) where, P is the pressure at required point and P 0 is the reference 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 dimension, 90 (case 2) and these values were found to be 0.23 and The force coefficients using wind tunnel Figure 6. Mean velocity distribution for case 1 & case 2.

5 CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model 227 Figure 7. Instantaneous streamlines for case 1. Figure 8. Instantaneous streamlines for 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 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 experimentation 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 visually. 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 behind the model at 12 stations for both the cases. The velocity 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 model and presented in terms of non-dimensionalised pressure 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 q = 0 and q = 90. Based on the CFD studies, the flow pattern 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. Following are the conclusions derived: l The force coefficients for both the test cases of wind flow normal to the longer plan dimension q = 0 and wind flow normal to the shorter plan dimension, q = 90 were found to be 0.23 and Corresponding to each of the directions, the force coefficients were derived based on force measurement using wind tunnel and were found to be 0.25

6 228 Selvi Rajan. S et al. Figure 9. Mean velocity defect profiles on wake centerline corresponding to case1 and case2. Figure 10. Pressure distribution over the model. and 1.2 respectively. These values were further compared well with the values available in the literature. l The predicted flow field around the model was examined using CFD as well as based on wind tunnel experiment. There was a very good comparison, as can be seen from Figures 7 and 8. l The CFD predictions provide good aid for fixing up the measurement points for velocity pressure measurement in all the directions besides providing better understanding on the flow pattern. l Such pre-experimental CFD study helps in reducing the number of repetitive experiments in the collection of data besides reducing the cost and time considerably when compared to the traditional approach of wind tunnel experiments, for certain type of typical selected studies. In the case, where the levels of turbulence intensities are of

7 CFD Analysis and Wind Tunnel Experiment on a Typical Launch Vehicle Model 229 high importance, it is imperative to resort to wind tunnel experiments. References [1] Murakami, S., Mochida, A. and Hayashi, Y., Examining the k- Model by Means of a Wind Tunnel Test and Large Eddy Simulation of the Turbulence Structure around a Cube, J. Wind Eng. Ind. Aerodyn., Vol. 35, pp (1990). [2] Tamura, T., Numerical Study of Aerodynamic Behavior of a Square Cylinder, J. Wind Eng. Ind. Aerodyn., Vol. 33, pp (1990). [3] Murakami, S., Numerical Simulation of Turbulent Flow Filed around Cubic Model Current Statues and Applications of k- Model and LES, J. Wind Eng. Ind. Aerodyn., Vol. 33, pp (1990). [4] Mukesh Kumar, Geospatial Evaluation of Biodiversity Pattern in Mining Landscape of Northern Chattisgarh, M. Tech Thesis, Remote Sensing and Geographic Information System Andhra University, Feb. India (2005). [5] Merzkirch, W., Flow Visualisation, Ed., 2 nd ed., Academic Press, New York (1987). [6] Weinstein, L. M., Large-Field Schlieren Visualisation from Wind Tunnel to Flight, Journal of Visualisation, Vol. 2, pp (2000). [7] Kompenhans, J., Raffel, M., Dieterle, L., Dewhirst, T., Vollmers, H., Ehrenfried, K., Willert, C., Pengel, K., Kahler, C., Schroder, A. and Ronneberger, O., Particle Image Velocimetry in Aerodynamics: Technology and Applications in Wind Tunnels, Journal of Visualization, Vol. 2, pp (2000). [8] STAR-CD version 3.15A manuals, Computational Dynamics Limited (2002). [9] David Sumner, Closely Spaced Circular Cylinders in Cross-Flow and a Universal Wake Number, Journal of Fluids Engineering, Vol. 126, pp (2004). [10] Ioannis Kitsios and John Lygeros, Computation for a Personnel Launch Vehicle Using Reachability, American Institute of Aeronautics and Astronautics Launchpad Abort Flight Envelope, HYCON-publications. [11] Experiment on Reducing Drag on an Aerospace Launch Vehicle, Dryden Flight Research Center, Edwards, California. Manuscript Received: Jul. 16, 2008 Accepted: Jun. 10, 2009