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Achieving high parallel performance for an unstructured unsteady turbomachinery CFD code

Published online by Cambridge University Press:  03 February 2016

N. Hills
N. Hills*
Affiliation:
University of Surrey, Guildford, UK
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Abstract

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This paper describes the work done to achieve high parallel performance for an unstructured, unsteady turbomachinery computational fluid dynamics (CFD) code. The aim of the work described here is to be able to scale problems to the thousands of processors that current and future machine architectures will provide. The CFD code is in design use in industry and is also used as a research tool at a number of universities. High parallel scalability has been achieved for a range of turbomachinery test cases, from steady-state hexahedral mesh cases to fully unsteady unstructured mesh cases. This has been achieved by a combination of code modification and consideration of the parallel partitioning strategy and resulting load balancing. A sliding plane option is necessary to run fully unsteady multistage turbomachinery test cases and this has been implemented within the CFD code. Sample CFD calculations of a full turbine including parts of the internal air system are presented.

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 111 , Issue 1117 , March 2007 , pp. 185 - 193
Copyright
Copyright © Royal Aeronautical Society 2007 

References

1. Denton, J.D. and Dawes, W.N., Computational fluid dynamics for turbomachinery design, Proc Istn Mech Engrs, 1999, 213 Part C, pp 107–204.Google Scholar
2. Ni, R.H. and Bogoian, J.C., Prediction of 3D multistage turbine flow field using a multigrid Euler solver, AIAA paper 89-0203, 1989.Google Scholar
3. Adamcyzk, J.J., Celestina, M., Beach, T.A. and Barnett, M., Simulation of viscous flow within a multistage turbine, ASME J Turbomachinery, 1990, 112.Google Scholar
4. Hah, C. and Wennerstrom, A., Three-dimensional flowfields inside a transonic compressor with swept blades, ASME J Turbomachinery, 1991, 113.Google Scholar
5. Dawes, W.N., Towards improved throughflow capability: the use of 3D viscous flow solvers in a multistage environment, ASME J Turbomachinery, 1992, 114.Google Scholar
6. Denton, J.D., The calculation of three-dimensional viscous flow through multistage turbomachinery, ASME J Turbomachinery, 1992, 114.Google Scholar
7. Jennions, I.K. and Turner, M.G., Three-dimensional Navier-Stokes computations of transonic fan using an explicit flow solver and an Implicit k-e Solver, ASME J Turbomachinery, 1993, 115.Google Scholar
8. Wallis, A.M., Denton, J.D. and Demargne, A.A., The control of shroud leakage flows to reduce aerodynamic losses in a low aspect ratio, shrouded axial flow turbine, ASME paper 2000-475, 2000.Google Scholar
9. Bohn, D.E, Balkowski, I., Ma, H. and Tuemmers, C., Influence of open and closed shroud cavities on the flowfield in a 2-Stage turbine with shrouded blades, ASME paper 2003-38436, 2003.Google Scholar
10. Rosic, B., Denton, J.D. and Pullan, G., The importance of shroud leakage modelling in multistage turbine flow calculations, ASME paper 2005-68469, 2005.Google Scholar
11. Gier, J., Stubert, B., Brouillet, B. and Devito, L., Interaction of shroud leakage flow and main flow in a three-stage LP turbine, ASME paper 2003-38025, 2003.Google Scholar
12. Cherry, D., Wadia, A., Beacock, R., Subramian, M. and Vitt, P., Analytical investigation of a low pressure turbine with and without flowpath endwall gaps, seals, and clearance features, ASME paper 2005-68492, 2005.Google Scholar
13. Chew, J.W., Hills, N.J., Hornsby, C. and Young, C., Recent developments in application of CFD to turbomachinery internal air systems, 5th European Turbomachinery Conference (ETC5), 2003.Google Scholar
14. Virr, G.P., Chew, J.W. and Coupland, J., Application of computational fluid dynamics to turbine disc cavities, ASME J Turbomachinery, 1993, 116, pp 701–708.Google Scholar
15. Hills, N.J., Chew, J.W. and Turner, A.B., Computational and mathematical modelling of turbine rim seal ingestion, ASME J of Turbomachinery, 124, 2002.Google Scholar
16. Cao, C., Chew, J.W., Millington, P.R. and Hogg, S.I., Interaction of rim seal and annulus flows in an axial flow turbine, ASME paper 2003-38368, 2003.Google Scholar
17. Jakoby, R., Zierer, T., Lindblad, K., Larsson, J., Devito, L., Bohn, D., Funcke, J. and Decker, A., Numerical simulation of the unsteady flow field in an axial gas turbine rim seal configuration. ASME paper 2004-53829, 2004.Google Scholar
18. Boudet, J., Autef, V.N.D., Chew, J.W., Hills, N.J. and Gentilhomme, O., Numerical simulation of rim seal flows in axial turbines, Aeronaut J, August 2005, (1089), 109, pp 361–372.Google Scholar
19. Spalart, P.R. and Allmaras, S.R., A one-equation turbulence model for aerodynamic flows, La Recherche Aerospatiale, 1, pp 5–21.Google Scholar
20. Moinier, P. and Giles, M.B., Preconditioned Euler and Navier-Stokes calculations on unstructured grids, 6th ICFD Conference on Numerical Methods for Fluid Dynamics, 1998, Oxford, UK.Google Scholar
21. Moinier, P., Algorithm Developments for an Unstructured Viscous Flow Solver, PhD thesis, 1999, University of Oxford, UK.Google Scholar
22. Martinelli, L., Calculations of Viscous Flows with a Multigrid Method, PhD. thesis, 1987, Dept of Mech and Aerospace Eng, Princeton University, USA.Google Scholar
23. Crumpton, P.I., Muller, J-D. and Giles, M.B., Edge-based multigrid schemes and preconditioning for hybrid grids. AIAA J, 40, pages 1954–1960, 2002.Google Scholar
24. Crumpton, P.I. and Giles, M.B.. Implicit time accurate solutions on unstructured dynamic grids. AIAA paper 95-1671, 1995.Google Scholar
25. Shahpar, S., Giacche, D. and Lapworth, L., Multi-objective design and optimisation of bypass outlet guide vanes. ASME paper GT-2003-38700, 2003.Google Scholar
26. Burgess, D.A., Crumpton, P.I. and Giles, M.B., A Parallel Framework for Unstructured Grid Solvers. In Decker, K.M. and Rehmann, R.M. (Eds), Programming Environments for Massively Parallel Distributed Systems, 1994, pp 97–106, Birkhauser.Google Scholar
27. Sunderam, V.S., PVM: A framework for parallel distributed computing, concurrency, Practice and Experience, 2, 1990, pp 315–339.Google Scholar
28. Mccoll, W.F., Scalable Computing. in Computer Science Today: Recent Trends and Developments, Springer-Verlag, 1995.Google Scholar
29. Valiant, L.G., A Bridging model for parallel computation. communications of the ACM, 1990, 33, pp 103–111.Google Scholar
30. Shahpar, S., Padram: Parametric design and rapid meshing system for turbomachinery optimisation, ASME paper GT-2003-38698, 2003.Google Scholar
31. Gropp, W.D., Kaushk, D.K., Keys, D.E., and Smith, B.F., High Performance Parallel Implicit CFD, Parallel Computing, 2001, 27, pp 337–362.Google Scholar
32. Karypsis, G. and Kumar, V., A FAST and high quality scheme for partitioning irregular graphs, SIAM J Scientific Computing, 1999, 20, pp 359–392.Google Scholar
33. Pallas high performance computing products, http://www.pallas.com Google Scholar
34. Rai, M.M., Unsteady 3D Navier-Stokes simulation of turbine rotorstator interaction, AIAA paper 87-2058, 1987.Google Scholar
35. Martelli, F., Unsteady flow modelling in a turbine stage, annals of the New York Academy of Sciences, 2000, 934, pp 80–95.Google Scholar
36. Karypsis, G. and Kumar, V., Multilevel algorithms for multi-constraint graph partitioning, Proc. Supercomputing ’98, 1998.Google Scholar