Skip to main content
Log in

Stochastic Shell Model for Turbulent Mixing of Multiple Scalars with Mean Gradients and Differential Diffusion

  • Published:
Flow, Turbulence and Combustion Aims and scope Submit manuscript

Abstract

In this paper, we develop a shell model for the velocity and scalar concentrations that, by design, is consistent with the eddy damped quasi-normal Markovian (EDQNM) model for multiple mixing scalars. We review the realizable form of the EDQNM model derived by Ulitsky and Collins (J Fluid Mech 412:303–329, 2000), which forms the basis for the shell model. The equations governing the velocity and scalar within each shell are stochastic ordinary differential equations with drift and diffusion terms chosen so that the velocity variance, velocity–scalar cross correlations, and scalar–scalar cross correlations within each shell precisely match the EDQNM model predictions. Consequently, shell averages can be thought of as a representation of the discrete three-dimensional spectrum. An advantage the shell model has over the original EDQNM equations is that the sum of each realization over the shells is a model for the fine-grained, joint velocity/scalar probability density function (PDF). Indeed, this provides some of the motivation for the development of the model. We cannot exploit this feature in the present study of the mixing of two scalars with uniform mean gradients, as the PDF is a joint Gaussian throughout (and hence the correlation matrix completely defines the distribution). The model is capable of predicting Lagrangian correlation functions for the scalar, scalar dissipation and velocity. We find the predictions of the model are in good qualitative agreement with direct numerical simulations by Yeung (J Fluid Mech 427:241–274, 2001). Eventually we will apply the shell model to scalars that are initially highly non-Gaussian (e.g., double delta function) and observe the relaxation towards a Gaussian. As the shell model contains information on the spectral distribution of the scalar field, the relaxation rate will depend upon the length and time scales of the turbulence and the scalar fields, as well as the molecular diffusivities of the species. The full capabilities of the PDF predictions of the model will be the subject of a future publication.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Pope, S.B.: PDF methods for turbulent reactive flows. Prog. Energy Combust. Sci. 11, 119–192 (1985)

    Article  MathSciNet  Google Scholar 

  2. Pope, S.B.: Lagrangian PDF methods for turbulent flows. Ann. Rev. Fluid Mech. 26, 23–63 (1994)

    Article  MathSciNet  Google Scholar 

  3. Kuznetsov, V.R., Sabel’nikov, V.A.: Turbulence and Combustion. Hemisphere (1990)

  4. Heinz, S.: Statistical Mechanics of Turbulent Flows. Springer (2003)

  5. Haworth, D.C.: Progress in probability density function methods for turbulent reacting flows. Prog. Energy Combust. Sci., 36, 168–259 (2010)

    Article  Google Scholar 

  6. Fox, R.O.: Computational Models for Turbulent Reacting Flows. Cambridge University Press, New York (2003)

    Book  Google Scholar 

  7. Mazumder, S., Modest, M.F.; A PDF approach to modeling turbulence-radiation interactions in nonluminous flames. Int. J. Heat Mass Transfer 42, 971–991 (1998)

    Article  Google Scholar 

  8. Li, G., Modest, M.F.: Investigation of turbulence-radiation interactions in reacting flows using a hybrid FV/PDF Monte Carlo method. In: Proceedings of the ICHMT 3rd Int. Sym. on Rad. Trans. (2001)

  9. Ren, Z., Pope, S.B.: Sensitivity calculations in PDF particle methods. Combust. Flame 153, 202–215 (2008)

    Article  Google Scholar 

  10. Subramaniam, S., Pope, S.B.: A mixing model for turbulent reactive flows based on Euclidean Minimum Spanning Trees. Combust. Flame 115, 487–514 (1998)

    Article  Google Scholar 

  11. Pope, S.B.: Turbulent Flows. Cambridge University Press, New York (2000)

    MATH  Google Scholar 

  12. Dopazo, C.: Probability density function approach for a turbulent axisymmetric heated jet. Centerline evolution. Phys. Fluids 18, 397–404 (1975)

    Article  MATH  Google Scholar 

  13. Warhaft, Z., Lumley, J.L.: An experimental study of the decay of temperature fluctuations in grid generated turbulence. J. Fluid Mech. 88, 659–684 (1978)

    Article  Google Scholar 

  14. Eswaran, V., Pope, S.B.: Direct numerical simulations of the turbulent mixing of a passive scalar. Phys. Fluids 31, 506–520 (1988)

    Article  Google Scholar 

  15. Juneja, A., Pope, S.B.: A DNS study of turbulent mixing of two passive scalars. Phys. Fluids 8, 2161–2184 (1996)

    Article  MATH  Google Scholar 

  16. Vaithianathan, T., Ulitsky, M., Collins, L.R.: Comparison between a spectral and PDF model for turbulent reacting flows. Proc. Comb. Inst. 29, 2139–2146 (2002)

    Article  Google Scholar 

  17. Meyers, R.E., O’Brien, E.E.: The joint PDF of a scalar and its gradient at a point in a turbulent flow. Combust. Sci. Technol. 26, 123 (1981)

    Article  Google Scholar 

  18. Gao, F.: An analytical solution for the scalar probability density function in homogeneous turbulence. Phys. Fluids, A 3, 511 (1991)

    Article  MATH  Google Scholar 

  19. Kuo, Y.-Y., O’Brien, E.E.: Two-point probability density function closure applied to a diffusive-reactive system. Phys. Fluids 24(2), 194–201 (1981)

    Article  MATH  Google Scholar 

  20. Ievlev, V.M.: Equations for finite-dimensional distributions of pulsating value possibilities in a turbulent flow. Dokl. Akad. Nauk SSSR 208, 1044–1047 (1973)

    Google Scholar 

  21. Fox, R.O., Yeung, P.K.: Improved Lagrangian mixing models for passive scalars in isotropic turbulence. Phys. Fluids 15, 961–985 (2003)

    Article  Google Scholar 

  22. Fox, R.O.: The Lagrangian spectral relaxation model of the scalar dissipation in homogeneous turbulence. Phys. Fluids 9, 2364–2386 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  23. Fox, R.O.: The Lagrangian spectral relaxation model for differential diffusion in homogeneous turbulence. Phys. Fluids 11, 1550–1571 (1999)

    Article  MATH  Google Scholar 

  24. Fox, R.O.: The Fokker-Planck closure for turbulent molecular mixing: Passive scalars. Phys. Fluids, A 4, 1230–1244 (1992)

    Article  MATH  Google Scholar 

  25. Fox, R.O.: Improved Fokker-Planck model for the joint scalar, scalar gradient PDF. Phys. Fluids, A 6, 334–348 (1994)

    Article  MATH  Google Scholar 

  26. Smith, L.L., Dibble, R.W., Talbot, L., Barlow, R.S., Carter, C.D.: Laser raman scattering measurements of differential molecular diffusion in nonreacting turbulent jets of H2/CO2 mixing with air. Phys. Fluids 7, 1455–1466 (1995)

    Article  Google Scholar 

  27. Yeung, P.K.: Multi-scalar triadic interactions in differential diffusion with and without mean scalar gradients. J. Fluid Mech. 321, 235 (1996)

    Article  MATH  Google Scholar 

  28. Saylor, J.R., Sreenivasan, K.R.: Differential diffusion in low Reynolds number water jets. Phys. Fluids 10, 1135–1146 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  29. Gledzer, E.B.: System of hydrodynamic type admitting two quadratic integrals of motion. Sov. Phys. Dokl. 18, 216–217 (1973)

    MATH  Google Scholar 

  30. Ohkitani, K., Yamada, M.: Temporal intermittency in the energy cascade process and local Lyapunov analysis in fully developed model of turbulence. Prog. Theor. Phys. 89, 329–341 (1989)

    Article  MathSciNet  Google Scholar 

  31. Biferale, L.: Shell models of energy cascade in turbulence. Ann. Rev. Fluid Mech. 35, 441–468 (2003)

    Article  MathSciNet  Google Scholar 

  32. Orszag, S.A.: Analytical theories of turbulence. J. Fluid Mech. 41, 363–386 (1970)

    Article  MATH  Google Scholar 

  33. Lesieur, M.: Turbulence in Fluids, Stochastic and Numerical Modeling. M. Nijhoff, Boston (1987)

    Google Scholar 

  34. Kraichnan, R.H.: The structure of isotropic turbulence at very high Reynolds numbers. J. Fluid Mech. 5, 497–543 (1959)

    Article  MATH  MathSciNet  Google Scholar 

  35. Andre, J.C., Lesieur, M.: Influence of helicity on the evolution of isotropic turbulence at high Reynolds number. J. Fluid Mech. 81, 187 (1977)

    Article  MATH  Google Scholar 

  36. Vignon, J.-M., Cambon, C.: Thermal spectral calculation using eddy-damped quasi-normal markovian theory. Phys. Fluids 23, 1935–1937 (1980)

    Article  Google Scholar 

  37. Herring, J.R., Schertzer, D., Lesieur, M., Newman, G.R., Chollet, J.P., Larcheveque, M.: A comparitive assessment of spectral closures as applied to passive scalar diffusion. J. Fluid Mech. 124, 411–438 (1982)

    Article  MATH  Google Scholar 

  38. Nakauchi, N., Oshima, H., Saito, Y.: A passive scalar convected by homogeneous axisymmetric turbulence. Phys. Fluids, A 1, 723 (1989)

    Article  MATH  Google Scholar 

  39. Herr, S., Wang, L.-P., Collins, L.R.: EDQNM model of a passive scalar with a uniform mean gradient. Phys. Fluids 8, 1588–1608 (1996)

    Article  MATH  Google Scholar 

  40. Ulitsky, M., Collins, L.R.: On constructing realizable, conservative mixed scalar equations using the eddy damped quasi-normal markovian theory. J. Fluid Mech. 412, 303–329 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  41. Ulitsky, M., Vaithianathan, T., Collins,. L.R.: A spectral study of differential diffusion of passive scalars in isotropic turbulence. J. Fluid Mech. 460, 1–38 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  42. Chen, H., Chen, S., Kraichnan, R.H.: Probability distribution of a stochastically advected scalar field. Phys. Rev. Lett. 63, 2657–2660 (1989)

    Article  Google Scholar 

  43. Pope, S.B.: Mapping closures for turbulent mixing and reaction. Theor. Comput. Fluid Dyn. 2, 255–270 (1991)

    Article  MATH  Google Scholar 

  44. Frankel, S., Jiang, T.-L., Givi, P.: Modeling of isotropic reacting turbulence by a hybrid mapping-EDQNM closure. AIChE J. 38, 535–543 (1992)

    Article  Google Scholar 

  45. She, Z.-S., Jackson, E.: Constrained Euler system for Navier-Stokes turbulence. Phys. Rev. Lett. 70(9), 1255–1258 (1993)

    Article  Google Scholar 

  46. Pouquet, A., Lesieur, M., Andre, J.C., Basdevant, C.: Evolution of high Reynolds number two-dimensional turbulence. J. Fluid Mech. 72, 305–319 (1975)

    Article  MATH  Google Scholar 

  47. Herring, J.R.: Approach of axisymmetric turbulence to isotropy. Phys. Fluids 17, 859 (1974)

    Article  MATH  Google Scholar 

  48. Klebaner, F.C.: Introduction to Stochastic Calculus with Applications. Imperial College Press (2005)

  49. Vaithianathan, T.: A New Multi-Scale Mixing Model for Turbulent Reacting Flows. PhD thesis, Penn State University (2003)

  50. Chang, C.-C.: Numerical solutions of stochastic differential equations with constant diffusion coefficients. Math. Comput. 49, 523–542 (1987)

    MATH  Google Scholar 

  51. Yeung, P.K.: Lagrangian characteristics of turbulence and scalar transport in direct numerical simulations. J. Fluid Mech. 427, 241–274 (2001)

    Article  MATH  Google Scholar 

  52. Xia, Y., Liu, Y., Vaithianathan, T., Collins, L.R.: Eddy damped quasi normal Markovian theory for chemically reactive scalars in isotropic turbulence. Phys. Fluids 22(4), 045103 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lance R. Collins.

Additional information

This paper is dedicated to my colleague, Professor Stephen B. Pope, on the occasion of his 60th birthday. Prof. Pope’s pioneering research into the use of probability density function (PDF) methods for chemically reacting turbulent flows has served as inspiration to a generation of scientists and engineers, and indeed motivates the present development of a multi-scale turbulent mixing model.—L. R. Collins

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xia, Y., Vaithianathan, T. & Collins, L.R. Stochastic Shell Model for Turbulent Mixing of Multiple Scalars with Mean Gradients and Differential Diffusion. Flow Turbulence Combust 85, 689–709 (2010). https://doi.org/10.1007/s10494-010-9261-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10494-010-9261-8

Keywords

Navigation