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Rotating turbulent flows form a challenging test case for large-eddy simulation (LES). We, therefore, propose and validate a new subgrid-scale (SGS) model for such flows. The proposed SGS model consists of a dissipative eddy viscosity term…

流体动力学 · 物理学 2019-04-30 Maurits H. Silvis , H. Jane Bae , F. Xavier Trias , Mahdi Abkar , Roel Verstappen

An innovative \textit{deep learning} approach has been adopted to formulate the eddy-viscosity for large eddy simulation (LES) of wall-bounded turbulent flows. A deep neural network (DNN) is developed which learns to evaluate the…

流体动力学 · 物理学 2019-05-31 Anikesh Pal

In this paper, we have used renormalized viscosity for performing large eddy simulations (LES) of decaying homogeneous and isotropic turbulence inside a periodic cube on coarse grids ($32^3$, $64^3$ and $128^3$) at initial Taylor Reynolds…

流体动力学 · 物理学 2018-04-25 Sumit Vashishtha , Anando Chatterjee , Abhishek Kumar , Mahendra K Verma

In this work we introduce a computational framework for determining optimal closures of the eddy-viscosity type for Large-Eddy Simulations (LES) of a broad class of PDE models, such as the Navier-Stokes equation. This problem is cast in…

流体动力学 · 物理学 2020-03-12 Pritpal Matharu , Bartosz Protas

Floods, tides and tsunamis are turbulent, yet conventional models are based upon depth averaging inviscid irrotational flow equations. We propose to change the base of such modelling to the Smagorinksi large eddy closure for turbulence in…

混沌动力学 · 物理学 2008-05-22 A. J. Roberts , D. J. Georgiev , D. V. Strunin

Compressible magnetohydrodynamic (MHD) turbulence is ubiquitous in astrophysical phenomena ranging from the intergalactic to the stellar scales. In studying them, numerical simulations are nearly inescapable, due to the large degree of…

流体动力学 · 物理学 2016-07-27 Dimitar G Vlaykov , Philipp Grete , Wolfram Schmidt , Dominik R G Schleicher

A previously developed modeling procedure for large eddy simulations (LESs) is extended to allow physical space implementations for inhomogeneous flows. The method is inspired by the well-established theoretical analyses and numerical…

流体动力学 · 物理学 2022-10-28 Guangrui Sun , J. Andrzej Domaradzki

Standard eddy viscosity models, while robust, cannot represent backscatter and have severe difficulties with complex turbulence not at statistical equilibrium. This report gives a new derivation of eddy viscosity models from an equation for…

数值分析 · 数学 2015-03-05 Nan Jiang , William Layton

Large-eddy simulations (LES) with an appropriate subgrid-scale (SGS) model provide a powerful tool for investigating real-world turbulence. The Smagorinsky model, one of the simplest and most used SGS models, often shows an over-dissipative…

流体动力学 · 物理学 2026-03-30 Nobumitsu Yokoi , Pablo D. Mininni , Annick Pouquet , Duane Rosenberg , Raffaele Marino

Large-eddy simulation (LES) is a well-established numerical technique, which resolves the most energetic turbulent fluctuations in the planetary boundary layers. Averaging these fluctuations, high-quality profiles of mean values and…

大气与海洋物理 · 物理学 2007-05-23 Igor N. Esau , Oyvind Byrkjedal

Most sub-grid scale (SGS) models employed in LES (large eddy simulation) formulations were originally developed for incompressible, single phase, inert flows and assume transfer of energy based on the classical energy cascade mechanism.…

流体动力学 · 物理学 2023-09-13 Jhon Cordova , Cesar Celis , Andres Mendiburu , Luis Bravo , Prashant Khare

Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct…

流体动力学 · 物理学 2023-12-13 Shengyu Chen , Tianshu Bao , Peyman Givi , Can Zheng , Xiaowei Jia

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…

流体动力学 · 物理学 2023-06-22 Mehdi Samiee , Ali Akhavan-Safaei , Mohsen Zayernouri

We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS)…

流体动力学 · 物理学 2026-04-13 Ben-Rui Xu , Ao Xu

We consider the question of fundamental limitations on the performance of eddy-viscosity closure models for turbulent flows, focusing on the Leith model for 2D {Large-Eddy Simulation}. Optimal eddy viscosities depending on the magnitude of…

流体动力学 · 物理学 2022-03-29 Pritpal Matharu , Bartosz Protas

Turbulence in compressible plasma plays a key role in many areas of astrophysics and engineering. The extreme plasma parameters in these environments, e.g. high Reynolds numbers, supersonic and super-Alfvenic flows, however, make direct…

Direct numerical simulations (DNS) are one of the main ab initio tools to study turbulent flows. However, due to their considerable computational cost, DNS are primarily restricted to canonical flows at moderate Reynolds numbers, in which…

流体动力学 · 物理学 2024-09-17 Arnab Moitro , Sai Sandeep Dammati , Alexei Y. Poludnenko

We formulate and implement the Euler equations with SGS dynamics and provide numerical tests of an SGS turbulence energy model that predicts the turbulent pressure of unresolved velocity fluctuations and the rate of dissipation for highly…

星系天体物理 · 物理学 2015-05-20 W. Schmidt , C. Federrath

A new tuning-free subgrid-scale model, termed `locally-averaged scale-dependent dynamic' (LASDD) model, is developed and implemented in large-eddy simulations (LESs) of stable boundary layers. The new model dynamically computes the…

大气与海洋物理 · 物理学 2016-08-16 Sukanta Basu , Fernando Porté-Agel

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

流体动力学 · 物理学 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien