Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-18T14:59:46.941Z Has data issue: false hasContentIssue false
  • English
  • Français

High-order detached-eddy simulation of external aerodynamics over an SAE notchback model

Part of: APISAT 2015

Published online by Cambridge University Press:  24 July 2017

A. Islam  and
B. Thornber
A. Islam*
Affiliation:
School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney Darlington, NSW 2006, Australia
B. Thornber
Affiliation:
School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney Darlington, NSW 2006, Australia
*
asiful.islam@sydney.edu.au
Get access Rights & Permissions [Opens in a new window]

Abstract

This research explores the modification and implementation of a Detached-Eddy Simulation (DES) in a high-order compressible solver and its application to automotive aerodynamics. This was conducted on a 20° SAE Reference Notchback Model with a Reynolds number of 2.23 × 105. This DES algorithm implemented within FLAMENCO, which is finite-volume research code operating over multi-block meshes, was used for all the simulations. The primary objectives were to capture unsteady flow features, separated coherent structures and also relax the meshing requirements to improve accessibility to turbulence-resolving methods for realistic configurations. This also aims to better understand the separated flow physics, especially around the base surfaces of the car. Simulations for three mesh refinement levels were compared to wind-tunnel measurements. Even on relatively coarse meshes (~7 m cells) for DES, time-averaged Cp was obtained with maximum errors of <8%.

Type
Research Article
Information
The Aeronautical Journal , Volume 121 , Issue 1243 , September 2017 , pp. 1342 - 1367
Copyright
Copyright © Royal Aeronautical Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This is an adaptation of a paper first presented at the 2015 Asia-Pacific International Symposium on Aerospace Technology in Cairns, Australia

References

REFERENCES

1. Sagaut, P. and Deck, S. A framework for aircraft conceptual design and environmental performance studies, Philosophical Transactions of the Royal Society of London, 2009, 367, pp 2849–2860, doi: 10.1098/rsta.2008.0269.Google Scholar
2. Spalart, P.R., Deck, S., Shur, M.L. and Squires, K.D. A new version of detached-eddy simulation, resistant to ambiguous grid densities, Theoretical Computational Fluid Dynamics, 2006, 20, (3), pp 181–195.CrossRefGoogle Scholar
3. Islam, M., Decker, F., de Villiers, E., Jackson, A., Gines, J., Grahs, T., Gitt-Gehrke, A. and Comas i Font, J. Application of the detached-Eddy simulation for automotive aerodynamics development, Society of automotive engineers, Tech Rep, SAE 2009-01-0333, 2009, doi: 10.4271/2009-01-0333.CrossRefGoogle Scholar
4. Chapman, D.R. Computational aerodynamics development and outlook, AIAA J, 1979, 17, (1293).CrossRefGoogle Scholar
5. Choi, H. and Moin, P. Grid-point requirements for large eddy simulation: Chapman’s estimates revisited, Physics of Fluids, 2012, 24, (011702), pp 1–5.CrossRefGoogle Scholar
6. Guilmineau, E., Deng, G. and Wackers, J. Numerical simulation with a DES approach for automotive flows, J of Fluids and Structures, 2011, 27, pp 807–816.CrossRefGoogle Scholar
7. Wood, D., Passmore, M. and Perry, A. Loughborough University Institutional Repository, Loughborough University, 2017. [Online]. Available: https://dspace.lboro.ac.uk/2134/13886. [Accessed: 20-Feb-2017].Google Scholar
8. Ashton, N. and Revell, A. Key factors in the use of DDES for the flow around a simplified car, Int J of Heat and Fluid Flow, 2015, 54, pp 236–249.CrossRefGoogle Scholar
9. Le Good, G. and Garry, K.P. On the use of reference models in automotive aerodynamics, Society of Automotive Engineers, Tech Rep, SAE 2004-01-1308, 2004, doi: 10.4271/2004-01-1308.CrossRefGoogle Scholar
10. Wood, D., Passmore, M. and Perry, A. Experimental data for the validation of numerical methods - SAE reference notchback model, SAE Int J of Passenger Cars - Mech Systems, 2014, 7, (1), pp 145–154.CrossRefGoogle Scholar
11. Shanmuganathan, S., Youngs, D.L., Griffond, J., Thornber, B. and Williams, R.J.R. Accuracy of high-order density-based compressible methods in low Mach vortical flows, Int J of Numerical Methods in Fluids, 2014, 74, pp 355–358.CrossRefGoogle Scholar
12. Garcia-Uceda Juarez, A., Raimo, A., Shapiro, E. and Thornber, B. Steady flow computations using a low mach fully compressible scheme, AIAA J, 2014, 52, (11), pp 2559–2575.CrossRefGoogle Scholar
13. Islam, A. and Thornber, B. Development and application of a novel RANS and implicit LES hybrid turbulence model for automotive aerodynamics, SAE Technical Paper 2016-01-1608, 2016, doi: 10.4271/2016-01-1608.CrossRefGoogle Scholar
14. Islam, A. and Thornber, B. A hybrid RANS-implicit LES method for external aerodynamics, Proceedings of the 19th Australasian Fluid Mechanics Conference, 2014, RMIT Australia. [Online]. Available: http://people.eng.unimelb.edu.au/imarusic/proceedings/19/54.pdf. [Accessed: 20-Dec-2016].Google Scholar
15. Thornber, B. and Zhou, Y. Energy transfer in the Richtmyer-Meshkov instability, Physical Review E, 86, (056302), 2012.CrossRefGoogle ScholarPubMed
16. Zhou, Y. and Thornber, B. A comparison of three approaches to compute the effective Reynolds number of the implicit Large-Eddy simulations, J Fluids Engineering, Transactions of the ASME, 2016, 138, (7).CrossRefGoogle Scholar
17. Leveque, R.J. Finite Volume Methods for Hyperbolic Problems, Cambridge Texts in Applied Mathematics, Cambridge University Press, London, 2002.CrossRefGoogle Scholar
18. Drikakis, D., Hahn, M., Mosedale, A. and Thornber, B. Large eddy Simulation using high-resolution and high-order methods, Philosophical Transactions of the Royal Soc of London, 2009, 367, pp 2985–2997.Google ScholarPubMed
19. Thornber, B., Mosedale, D., Drikakis, D. and Williams, R.J.R. An improved reconstruction method for compressible flows with low Mach number features, J Computational Physics, 2008, 227, pp 4873–4894.CrossRefGoogle Scholar
20. Thornber, B., Drikakis, D., Williams, R.J.R. and Youngs, D. On entropy generation and dissipation of kinetic energy in high-resolution shock-capturing schemes, J Computational Physics, 2008, 10, pp 4853–4872.CrossRefGoogle Scholar
21. Thornber, B. and Drikakis, D. Implicit Large-Eddy simulation of a deep cavity using high-resolution methods, AIAA J, 2008, 46, (10), pp 2634–2645.CrossRefGoogle Scholar
22. Thornber, B., Starr, M. and Drikakis, D. Implicit Large Eddy simulation of ship airwakes, The Aeronautical J, 2010, 114, pp 715–736.CrossRefGoogle Scholar
23. Axelsson, N., Ramnefors, M. and Gustafsson, R. Accuracy in computational aerodynamics part I: Stagnation pressure, Society of Automotive Engineers, SAE Technical Report 980037, International Congress and Exposition, 23–26 February 1998, doi: 10.4271/980037.CrossRefGoogle Scholar
24. Nader, A., Islam, A. and Thornber, B. A comparative aerodynamic investigation of a 20° SAE notchback model, Applied Mech and Materials, 2015, 846, pp 79–84.CrossRefGoogle Scholar
25. Carr, G.W. and Stapleford, W.R. Blockage effects in automotive wind-tunnel testing, SAE Technical Paper Series 860093, 1985, doi: 10.4271/860093.CrossRefGoogle Scholar
26. Rana, Z., Thornber, B. and Drikakis, D. On the importance of generating accurate turbulent boundary conditions for unsteady simulations, J Turbulence, 2011, 12, (35), pp 1–39.CrossRefGoogle Scholar
27. Toro, E., Spruce, M. and Speares, W. Restoration of the contact surface in the HLLC-Riemann solver, Shock Waves, 1994, 4, (1), pp 25–34.CrossRefGoogle Scholar
28. Godunov, S.K. A finite-difference method for the computation of discontinuous solutions of the equations of fluid dynamics, Matematicheskiĭ Sbornik. Novaya Seriya, 1959, 47, (89), pp 271–306.Google Scholar
29. Kim, K. and Kim, C. Accurate, efficient and monotonic numerical methods for multi-dimensional compressible flows part ii. Multi-dimensional limiting process, J Computational Physics, 2005, 208, pp 570–615.CrossRefGoogle Scholar
30. Harten, A., Lax, P. and van Leer, B. On upstream differencing and Godunov-type schemes for hyperbolic conservation laws, SIAM Review, 1983, 25, (1), pp 35–61.CrossRefGoogle Scholar
31. Thornber, B. and Drikakis, D. Numerical dissipation of upwind schemes in low Mach flow, Int J for Numerical Methods in Fluids, 2007, 56, (8), pp 1535–1541.CrossRefGoogle Scholar
32. Spiteri, R.J. and Ruuth, S.J. A class of optimal strong-stability preserving time discretisation methods. SIAM J of Numerical Analysis, 2002, 40, (2), pp 469–491.CrossRefGoogle Scholar
33. Burgess, N.K. and Mavripalis, D. Robust computation of turbulent flows using a discontinuous Galerkin method, 50th AIAA Aerospace Sciences Meeting and Exhibit, 9–12 January 2012, Nashville, Tennessee, US, doi: 10.2514/6.2012-457.CrossRefGoogle Scholar
34. Gaylard, A., Howell, J. and Garry, K. Observation of flow asymmetry over the rear of notchback vehicles, SAE Technical Paper, 2007-01-0900, 2007, doi: 10.4271/2007-01-0900.CrossRefGoogle Scholar
35. Hunt, J.C.R., Wray, A. and Moin, P. Eddies, stream, and convergence zones in turbulent flows, Center for Turbulence Research, Research Report CTR-S88. [Online]. Available: https://web.stanford.edu/group/ctr/Summer/201306111537.pdf. [Accessed: 20-Dec-2016].Google Scholar