Tempered Fractional LES Modeling

Abstract

The presence of nonlocal interactions and intermittent signals in the homogeneous isotropic turbulence grant multi-point statistical functions a key role in formulating a new generation of large-eddy simulation (LES) models of higher fidelity. We establish a tempered fractional-order modeling framework for developing nonlocal LES subgrid-scale models, starting from the kinetic transport. We employ a tempered Lévy-stable distribution to represent the source of turbulent effects at the kinetic level, and we rigorously show that the corresponding turbulence closure term emerges as the tempered fractional Laplacian, $(\Delta +\lambda {)}^{\alpha }(\cdot )$, for $\alpha \in (0,1)$, $\alpha \ne \frac{1}{2}$, and $\lambda >0$ in the filtered Navier-Stokes equations. Moreover, we prove the frame invariant properties of the proposed model, complying with the subgrid-scale stresses. To characterize the optimum values of model parameters and infer the enhanced efficiency of the tempered fractional subgrid-scale model, we develop a robust algorithm, involving two-point structure functions and conventional correlation coefficients. In an a priori statistical study, we evaluate the capabilities of the developed model in fulfilling the closed essential requirements, obtained for a weaker sense of the ideal LES model (Meneveau 1994). Finally, the model undergoes the a posteriori analysis to ensure the numerical stability and pragmatic efficiency of the model.

28 pages, 10 figures, 3 tables

References in corpus (3)

• A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence
• Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows
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Cited by in corpus (2)

• A data-driven dynamic nonlocal subgrid-scale model for turbulent flows
• Dynamic Nonlocal Passive Scalar Subgrid-Scale Turbulence Modeling