Reaction analogy based forcing for incompressible scalar turbulence

We present a novel reaction analogy (RA) based forcing method for generating stationary scalar fields in incompressible turbulence. The new method can produce more general scalar PDFs (e.g. double-delta) than current methods, while ensuring that scalar fields remain bounded, unlike existent forcing methodologies that can potentially violate naturally existing bounds. Such features are useful for generating initial fields in non-premixed combustion or for studying non-Gaussian scalar turbulence. The RA method mathematically models hypothetical chemical reactions that convert reactants in a mixed state back into its pure unmixed components. Various types of chemical reactions are formulated and the corresponding mathematical expressions derived such that the reaction term is smooth in the scalar space and is consistent with mass conservation. For large values of the scalar dissipation rate, the method produces statistically steady double-delta scalar PDFs. Quasi-uniform, Gaussian, and stretched exponential scalar statistics are recovered for smaller values of the scalar dissipation rate. The shape of the scalar PDF can be further controlled by changing the stoichiometric coefficients of the reaction. The ability of the new method to produce fully developed passive scalar fields with quasi-Gaussian PDFs is also investigated, by exploring the convergence of the third order mixed structure function to the "four-thirds" Yaglom's law.

[1]  Daniel Livescu,et al.  Turbulence structure behind the shock in canonical shock–vortical turbulence interaction , 2014, Journal of Fluid Mechanics.

[2]  F. Spellman Combustion Theory , 2020 .

[3]  G. Eyink,et al.  Recovering isotropic statistics in turbulence simulations: the Kolmogorov 4/5th law. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Y. Kaneda,et al.  Study of High-Reynolds Number Isotropic Turbulence by Direct Numerical Simulation , 2009 .

[5]  Paul E. Dimotakis,et al.  Transition stages of Rayleigh–Taylor instability between miscible fluids , 2000, Journal of Fluid Mechanics.

[6]  Toshiyuki Gotoh,et al.  Inertial-range intermittency and accuracy of direct numerical simulation for turbulence and passive scalar turbulence , 2007, Journal of Fluid Mechanics.

[7]  D. Livescu,et al.  Numerical simulations of two-fluid turbulent mixing at large density ratios and applications to the Rayleigh–Taylor instability , 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[8]  L. Mydlarski,et al.  Effect of the scalar injection mechanism on passive scalar structure functions in a turbulent flow. , 2009, Physical review letters.

[9]  P. Moin,et al.  Constant-energetics physical-space forcing methods for improved convergence to homogeneous-isotropic turbulence with application to particle-laden flows , 2016 .

[10]  M. Petersen,et al.  Forcing for statistically stationary compressible isotropic turbulence , 2010 .

[11]  Jayesh,et al.  Probability distribution of a passive scalar in grid-generated turbulence. , 1991, Physical review letters.

[12]  Nilanjan Chakraborty,et al.  Scalar Dissipation Rate Modeling and its Validation , 2009 .

[13]  Diego Donzis,et al.  High-Reynolds-number simulation of turbulent mixing , 2005 .

[14]  P. Dimotakis The mixing transition in turbulent flows , 2000, Journal of Fluid Mechanics.

[15]  C. Beguier,et al.  Ratio of scalar and velocity dissipation time scales in shear flow turbulence , 1978 .

[16]  L. Luo,et al.  TIME-DEPENDENT ISOTROPIC TURBULENCE , 2003, Proceeding of Third Symposium on Turbulence and Shear Flow Phenomena.

[17]  J. C. Vassilicos,et al.  Energy dissipation and flux laws for unsteady turbulence , 2015 .

[18]  Yukio Kaneda,et al.  High-resolution direct numerical simulation of turbulence , 2006 .

[19]  S. Cantrell,et al.  The Theory and Applications of Reaction-Diffusion Equations: Patterns and Waves , 1997 .

[20]  J. D. Li,et al.  The diffusion of conserved and reactive scalars behind line sources in homogeneous turbulence , 1996, Journal of Fluid Mechanics.

[21]  R. Antonia,et al.  Comparison between kinetic energy and passive scalar energy transfer in locally homogeneous isotropic turbulence , 2012 .

[22]  D. Livescu,et al.  Vorticity dynamics after the shock–turbulence interaction , 2016 .

[23]  Eric D. Siggia,et al.  Scalar turbulence , 2000, Nature.

[24]  Stephen B. Pope,et al.  Direct numerical simulation of a passive scalar with imposed mean gradient in isotropic turbulence , 1996 .

[25]  Charles Meneveau,et al.  Linear forcing in numerical simulations of isotropic turbulence , 2005 .

[26]  K. Alvelius,et al.  RANDOM FORCING OF THREE-DIMENSIONAL HOMOGENEOUS TURBULENCE , 1999 .

[27]  G. Eyink Locality of turbulent cascades , 2005 .

[28]  Toshiyuki Gotoh,et al.  Statistics of a passive scalar in homogeneous turbulence , 2004 .

[29]  Katepalli R Sreenivasan,et al.  Extreme events in computational turbulence , 2015, Proceedings of the National Academy of Sciences.

[30]  T. Lundgren Linearly Forced Isotropic Turbulence , 2003 .

[31]  Implicit large-eddy simulation of passive scalar mixing in statistically stationary isotropic turbulence , 2013 .

[32]  Peyman Givi,et al.  Non-Gaussian scalar statistics in homogeneous turbulence , 1996, Journal of Fluid Mechanics.

[33]  J. Ristorcelli,et al.  Variable-density mixing in buoyancy-driven turbulence , 2007, Journal of Fluid Mechanics.

[34]  Stephen B. Pope,et al.  A Rational Method of Determining Probability Distributions in Turbulent Reacting Flows , 1979 .

[35]  S. Verma,et al.  A novel forcing technique to simulate turbulent mixing in a decaying scalar field , 2013 .

[36]  O. Desjardins,et al.  Technique for forcing high Reynolds number isotropic turbulence in physical space , 2018 .

[37]  S. Tavoularis,et al.  Scalar probability density function and fine structure in uniformly sheared turbulence , 2002, Journal of Fluid Mechanics.

[38]  S. Pope,et al.  Direct numerical simulation of a statistically stationary, turbulent reacting flow , 1999 .

[39]  R. Onishi,et al.  Origin of the imbalance between energy cascade and dissipation in turbulence. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  D. Chung,et al.  Direct numerical simulation and large-eddy simulation of stationary buoyancy-driven turbulence , 2009, Journal of Fluid Mechanics.

[41]  Daniel Livescu,et al.  Self-contained filtered density function , 2017 .

[42]  T. Gotoh,et al.  Power and nonpower laws of passive scalar moments convected by isotropic turbulence. , 2015, Physical review letters.

[43]  Robert McDougall Kerr,et al.  Higher-order derivative correlations and the alignment of small-scale structures in isotropic numerical turbulence , 1983, Journal of Fluid Mechanics.

[44]  Z. Warhaft Passive Scalars in Turbulent Flows , 2000 .

[45]  Passive-scalar wake behind a line source in grid turbulence , 2000, Journal of Fluid Mechanics.

[46]  Toshiyuki Gotoh,et al.  Universality and anisotropy in passive scalar fluctuations in turbulence with uniform mean gradient , 2011 .

[47]  Tongming Zhou,et al.  A generalization of Yaglom's equation which accounts for the large-scale forcing in heated decaying turbulence , 1999 .