Advertisement

The European Physical Journal Special Topics

, Volume 171, Issue 1, pp 167–171 | Cite as

Entropic, LES and boundary conditions in lattice Boltzmann simulations of turbulence

  • G. Vahala
  • B. Keating
  • M. Soe
  • J. Yepez
  • L. Vahala
  • S. Ziegeler
Article

Abstract

Large scale (16003-grid) entropic lattice Boltzmann (ELB) simulations are performed on the 27-bit model at sufficiently high Reynolds numbers to find intermittency corrections to the Kolmogorov k -5/3 inertial spectrum. Even though the transport coefficients in ELB and in the Large Eddy Simulation (LES) lattice Boltzmann schemes have very different origins, there are strong similarities in their turbulence statistics from 5123-grid simulations. A new LB moment-space boundary condition algorithm is tested on the 2D backstep problem, with excellent agreement with experimental data even up to a Reynolds number of 800.

Keywords

Large Eddy Simulation European Physical Journal Special Topic High Reynolds Number Reattachment Length Smagorinsky Constant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. I.V. Karlin, A. Ferrante, H.C. Ottinger, Europhys. Lett. 4, 182 (1999)Google Scholar
  2. S. Ansumali, I.V. Karlin, Phys. Rev. E 62, 7999 (2000); 65, 056312 (2000)Google Scholar
  3. S. Ansumali, I.V. Karlin, Phys. Rev. Lett. 95, 260604 (2005)Google Scholar
  4. B.M. Boghosian, J. Yepez, P.V. Coveney, A. Wagner, Proc. R. Soc. Lon. Ser. A 457, 717 (2001)Google Scholar
  5. B.M. Boghosian, P.J. Love, J. Yepez, P.V. Coveney, Physica D 193, 169 (2004)Google Scholar
  6. B. Keating, G. Vahala, J. Yepez, M. Soe, L. Vahala, Phys. Rev. E 75, 036712 (2007)Google Scholar
  7. S. Succi, Lattice Botlzmann Equation for Fluid Dynamics and Beyond (Oxford, 2001)Google Scholar
  8. J. Smagorinsky, Mon. Weather Rev. 91, 99 (1963)Google Scholar
  9. S. Hou, J. Sterling, S. Chen, G.D. Doolen, in Pattern Formation and Lattice Gas Automata, edited A.T. Lawniczak, R. Karpal in Field Inst. Commun. 6, 151 (1996)Google Scholar
  10. H. Yu, S.S. Girimaji, L.-S. Luo, J. Computat. Phys. 209, 599 (2005)Google Scholar
  11. S. Kida, Y. Murakami, Phys. Fluids 30, 2030 (1987)Google Scholar
  12. Y. Kaneda, T. Ishihara, M. Yokokawa, K. Itakura, A. Uno, Phys. Fluids 15, L21 (2005)Google Scholar
  13. P. Lallemand, L.-S. Luo, Phys. Rev. E 61, 6546 (2000)Google Scholar
  14. Q. Zou, X. He, Phys. Fluids 9, 1591 (1997)Google Scholar
  15. B.F. Armaly, F. Durst, J.C.F. Pereira, B. Schonung, J. Fluid Mech. 127, 473 (1983)Google Scholar
  16. S.S. Chikatamarla, S. Ansumali, I.V. Karlinr, Europhys. Lett. 7, 215 (2006)Google Scholar
  17. S. Ubertini, S. Succi, Comput. Fluid Dyn. 5, 85 (2005)Google Scholar
  18. L.K. Kaiktsis, G.E. Karniadakis, S.A. Orszag, J. Fluid Mech. 231, 501 (1991)Google Scholar

Copyright information

© EDP Sciences and Springer 2009

Authors and Affiliations

  • G. Vahala
    • 1
  • B. Keating
    • 2
  • M. Soe
    • 3
  • J. Yepez
    • 4
  • L. Vahala
    • 5
  • S. Ziegeler
    • 6
  1. 1.Department of PhysicsWilliamsburgUSA
  2. 2.Department of Ocean and Resources Eng.University of Hawaii at ManoaHonoluluUSA
  3. 3.Department of Mathematics and PhysicsRogers State UniversityClaremoreUSA
  4. 4.Air Force Research LaboratoryHanscom AFBUSA
  5. 5.Department of Electrical & Computer EngineeringOld Dominion UniversityNorfolkUSA
  6. 6.High Performance Computing Modernization Program, Mississippi State UniversityOktibbehaUSA

Personalised recommendations