English

Multi-scale turbulence modeling and maximum information principle. Part 2

Fluid Dynamics 2014-01-08 v3

Abstract

We consider two-dimensional homogeneous shear turbulence within the context of optimal control, a multi-scale turbulence model containing the fluctuation velocity and pressure correlations up to the fourth order; The model is formulated on the basis of the Navier-Stokes equations, Reynolds average, the constraints of inequality from both physical and mathematical considerations, the turbulent energy density as the objective to be maximized, and the fourth order correlations as the control variables. Without imposing the maximization and the constraints, the resultant equations of motion in the Fourier wave number space are formally solved to obtain the transient state solutions, the asymptotic state solutions and the evolution of a transient toward an asymptotic under certain conditions. The asymptotic state solutions are characterized by the dimensionless exponential time rate of growth 2σ2\sigma which has an upper bound of 2σmax2\sigma_{\max} = 0; The asymptotic solutions can be obtained from a linear objective convex programming. For the asymptotic state solutions of the reduced model containing the correlations up to the third order, the optimal control problem reduces to linear programming with the primary component of the third order correlations or a related integral quantity as the control variable; the supports of the second and third order correlations are estimated for the sake of numerical simulation; the existence of feasible solutions is demonstrated when the related quantity is the control variable. The relevance of the formulation to flow stability analysis is suggested.

Keywords

Cite

@article{arxiv.1307.4888,
  title  = {Multi-scale turbulence modeling and maximum information principle. Part 2},
  author = {L. Tao and M. Ramakrishna},
  journal= {arXiv preprint arXiv:1307.4888},
  year   = {2014}
}

Comments

58 pages, 4 figures, Document updated: Mathematical arguments included to show the convexity of the quadratic constraints. A new set of constraints of inequality added, which requires that the maximum exponential growth rate in the asymptotic state be zero. In the case of the asymptotic state solutions for the reduced model, feasible solutions are shown to be existent. Other minor corrections

R2 v1 2026-06-22T00:53:37.967Z