Novel mixed approximate deconvolution subgrid-scale models for large-eddy simulation

Fuente: arXiv
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Auteurs principaux: Amani, Ehsan, Molaei, Mohammad Bagher, Ghorbani, Morteza
Format: Preprint
Publié: 2025
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author Amani, Ehsan
Molaei, Mohammad Bagher
Ghorbani, Morteza
author_facet Amani, Ehsan
Molaei, Mohammad Bagher
Ghorbani, Morteza
contents Approximate Deconvolution (AD) has emerged as a promising closure for Large-Eddy Simulation (LES) in complex multi-physics flows, where the conventional pure Dynamic Eddy-Viscosity (DEV) models experience issues. In this research, we propose novel improved mixed hard-deconvolution or secondary-regularization models and compare their performance with the existing standard mixed AD-DEV and penalty-term regularizations. For this aim, five consistency criteria, based on the properties of the modeled sub-filter-scale stress in limit conditions, are introduced for the first time. It is proved that the conventional hard-deconvolution models do not adhere to a couple of important primary criteria. Furthermore, through a priori and a posteriori analyses of Burgers turbulence and turbulent channel flow, it is manifested that the inconsistency with the primary criteria can result in larger modeling errors, the over-prediction and pile-up of kinetic energy in eddies of a length scale between the explicit filter width and grid size, and even the solution instability. On the other hand, the favorable characteristics of the new mixed models, in terms of the consistency criteria, significantly improve the accuracy of the predictions, the solution stability, and even the computational cost, particularly for one of the new models called mixed Alternative-DEV (A-DEV).
format Preprint
id arxiv_https___arxiv_org_abs_2511_09697
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Novel mixed approximate deconvolution subgrid-scale models for large-eddy simulation
Amani, Ehsan
Molaei, Mohammad Bagher
Ghorbani, Morteza
Fluid Dynamics
Approximate Deconvolution (AD) has emerged as a promising closure for Large-Eddy Simulation (LES) in complex multi-physics flows, where the conventional pure Dynamic Eddy-Viscosity (DEV) models experience issues. In this research, we propose novel improved mixed hard-deconvolution or secondary-regularization models and compare their performance with the existing standard mixed AD-DEV and penalty-term regularizations. For this aim, five consistency criteria, based on the properties of the modeled sub-filter-scale stress in limit conditions, are introduced for the first time. It is proved that the conventional hard-deconvolution models do not adhere to a couple of important primary criteria. Furthermore, through a priori and a posteriori analyses of Burgers turbulence and turbulent channel flow, it is manifested that the inconsistency with the primary criteria can result in larger modeling errors, the over-prediction and pile-up of kinetic energy in eddies of a length scale between the explicit filter width and grid size, and even the solution instability. On the other hand, the favorable characteristics of the new mixed models, in terms of the consistency criteria, significantly improve the accuracy of the predictions, the solution stability, and even the computational cost, particularly for one of the new models called mixed Alternative-DEV (A-DEV).
title Novel mixed approximate deconvolution subgrid-scale models for large-eddy simulation
topic Fluid Dynamics
url https://arxiv.org/abs/2511.09697