Advertisement

Hierarchical Zonal Industrial Turbulence and Geometry Modelling Framework

  • P. G. TuckerEmail author
Conference paper
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 143)

Abstract

In a hierarchical fashion both the handling of turbulence and geometry are considered. The latter is necessary to help more economically deal with the increasingly coupled nature of many aerodynamic problems and also the drive towards considering ever increasing levels of geometrical complexity. The hybridization of RANS (Reynolds Averaged Navier-Stokes) and LES (Large Eddy Simulation), in various forms is explored. In relation to this, a taxonomy is presented. These aspects have all been presented here with a focus more on turbomachinery. The design needs for future engines is explored and it is discussed how these need to be met in a very integrated way, encompassing global installations all the way to avionics systems. However, it is believed that the applicability of these ideas goes beyond turbomachinery and is relevant to many other industrial applications. It is expected that the combination of these ideas will allow engineers to appropriately perform eddy resolving simulations in systems where there is significant aerodynamic coupling and a high level of geometrical complexity. The proposed unified framework could be exploited all the way through initial fast preliminary design to final numerical test involving various bespoke combinations of hierarchical components.

References

  1. 1.
    Lighthill, M.J.: On sound generated aerodynamically I. General Theor. Proc. Royal Soc. Ser. A 211, 564–587 (1952)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Mayle, R.: The role of laminar-turbulent transition in gas turbine engines. ASME J. Turbomach. 113, 509–537 (1991)CrossRefGoogle Scholar
  3. 3.
    Tucker, P.G., Eastwood, S., Klostermeier, C., Jefferson-Loveday, R., Tyacke, J., Liu, Y.: Hybrid LES approach for practical turbomachinery flows: part 1—hierarchy and example simulations. ASME J. Turbomach. 134(2), 021023 (10 pages) (2011)Google Scholar
  4. 4.
    Mouret, G.: Adaptation of phase-lagged boundary conditions to large-eddy simulation in turbomachinery configurations. Doctorat De L’universit´E De Toulouse (2016)Google Scholar
  5. 5.
    Wang, Z.J.: High-order computational fluid dynamics tools for aircraft design. Phil. Trans. R. Soc. A 2014 372 20130318 (2014).  https://doi.org/10.1098/rsta.2013.0318. (Published 14 July)
  6. 6.
    Menter, F.R, Kuntz, M., Bender R.: A Scale-Adaptive Simulation Model for Turbulent Flow Predictions. AIAA Paper 2003-0767 (2003)Google Scholar
  7. 7.
    Spalart, P.R.: Strategies for turbulence modelling and simulations. Engineering Turbulence Modelling and Experiments 4, Proceedings of the 4th International Symposium on Engineering Turbulence Modelling and Measurements; Ajaccio, Corsica, France, 24–26 May, pp. 3–17 (1999)Google Scholar
  8. 8.
    Holgate, J., Skillen, A., Craft, T., Revell, A.A. (2018) Review of embedded large eddy simulation for internal flows. Arch. Comput. Meth. Eng. 1–18 (2018)Google Scholar
  9. 9.
    Tucker, P.G.: Computation of unsteady turbomachinery flows: part 2—LES and hybrids. Prog. Aerosp. Sci. 47, 546–569 (2011)CrossRefGoogle Scholar
  10. 10.
    Tucker, P.G.: Unsteady Computational Fluid Dynamics in Aeronautics. Springer, ISBN 978-94-007-7048-5 (2013)Google Scholar
  11. 11.
    Cao, T., Hield, P., Tucker, P.G.: Hierarchical Immersed Boundary Method with Smeared Geometry. AIAA J. Propul. Power.  https://doi.org/10.2514/1.b36190 (2017)
  12. 12.
    Boris, J.P., Grinstein, F.F., Oran, E.S., Kolbe, R.L.: New insights into large eddy simulation. Fluid Dyn. Res. 10(4–6), 199–228 (1992)CrossRefGoogle Scholar
  13. 13.
    Pullan, G.: Introduction to numerical methods for predicting turbomachinery flows. Cambridge University Turbomachinery Course Notes (2008)Google Scholar
  14. 14.
    Tucker, P.G.: Advanced Computational Fluid and Aerodynamics. Cambridge University Press. ISBN: 9781107428836 (2016)Google Scholar
  15. 15.
    Stripf, M., Schulz, A., Bauer, H.-J., Wittig, S.: Extended models for transitional rough wall boundary layers with heat transfer—Part I: model formulations. J. Turbomach. 131(3), 031016 (Apr 20) (10 pages).  https://doi.org/10.1115/1.2992511(2009)
  16. 16.
    Berton, J.J.: System noise prediction of the DGEN 380 turbofan engine. AIAA Aviation 2015 22–26 June 2015, Dallas, Texas 21st AIAA/CEAS Aeroacoustics Conference AIAA 2015-2516 (2015)Google Scholar
  17. 17.
    Fried, E., Idelchik, I.E.: Flow Resistance: A Design Guide for Engineers. New York, Hemisphere (1989)Google Scholar
  18. 18.
    Liu, Y., Tucker, P.G.: Contrasting zonal LES and non-linear zonal URANS models when predicting a complex electronics system flow. Int. J. Numer. Meth. Eng. 71, 1–24 (2007)Google Scholar
  19. 19.
    Liu, Y., Tucker, P.G., Kerr, R.M.: Linear and non-linear large-eddy simulations of a plane jet. Comput. Fluids 37, 439–449 (2008)CrossRefGoogle Scholar
  20. 20.
    Tyacke, J.C., Mahak, M., Tucker, P.G.: Large scale, multi-fidelity, multi-physics, hybrid RANS-LES of an installed aeroengine. AIAA J. Propul. Power 32(4), 1–12 (2016).  https://doi.org/10.2514/1.b35947

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of EngineeringThe University of Cambridge, Department of EngineeringCambridgeUK

Personalised recommendations