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By combining AI and fluid physics, we discover a closed-form closure for 2D turbulence from small direct numerical simulation (DNS) data. Large-eddy simulation (LES) with this closure is accurate and stable, reproducing DNS statistics…

Atmospheric and Oceanic Physics · Physics 2026-01-21 Karan Jakhar , Yifei Guan , Pedram Hassanzadeh

A new methodology based on energy flux similarity is suggested in this paper for large eddy simulation (LES) of transitional and turbulent flows. Existing knowledge reveals that the energy cascade generally exists in transitional and…

Fluid Dynamics · Physics 2019-10-31 Han Qi , Xinliang Li , Hao Zhou , Changping Yu

Over the past 30 years, the cell-centred finite volume method has developed to become a viable alternative to the finite element method in the field of computational solid mechanics. The current article presents an open-source toolbox for…

Numerical Analysis · Mathematics 2018-09-05 P. Cardiff , A. Karač , P. De Jaeger , H. Jasak , J. Nagy , A. Ivanković , Ž. Tuković

The goal of this paper is to test solids4Foam, the fluid-structure interaction (FSI) toolbox developed for foam-extend (a branch of OpenFOAM), and assess its flexibility in handling more complex flows. For this purpose, we consider the…

Fluid Dynamics · Physics 2021-05-04 Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

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…

Fluid Dynamics · Physics 2020-03-12 Pritpal Matharu , Bartosz Protas

The energy balance of a partially molten rocky planet can be expressed as a non-linear diffusion equation using mixing length theory to quantify heat transport by both convection and mixing of the melt and solid phases. In this formulation…

Earth and Planetary Astrophysics · Physics 2017-11-22 Dan J. Bower , Patrick Sanan , Aaron S. Wolf

This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by…

Computational Engineering, Finance, and Science · Computer Science 2018-02-14 Jean-Baptiste Chapelier , Bono Wasistho , Carlo Scalo

Two widely used sub-grid scale models, the standard and the dynamic Smagorinsky models were tested in a simulation of the flow in a thermally driven 3D cavity at Rayleigh number of Ra=1E9. The main focus of the research is the response of…

Fluid Dynamics · Physics 2021-10-04 M. A. Sayed , A. Dehbi , M. Hadžiabić , B. Ničeno , K. Mikityuk

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

The predictive numerical simulation of supersonic turbulent combustion, in which the turbulent intensity is high and the fuel/air mixture is near the flammability limit, remains challenging. An investigation of subgrid mixing timescale…

Fluid Dynamics · Physics 2023-06-21 Jian An , Jieli Wei , Jian Zhanga , Hua Zhou , Zhuyin Ren

We introduce a data-driven learning framework that assimilates two powerful ideas: ideal large eddy simulation (LES) from turbulence closure modeling and neural stochastic differential equations (SDE) for stochastic modeling. The ideal LES…

The present study is concerned with large-eddy simulations (LES) of supersonic jet flows. The work addresses, in particular, the simulation of a perfectly expanded free jet flow with an exit Mach number of 1.4 and an exit temperature equal…

Fluid Dynamics · Physics 2023-01-05 D. F. Abreu , C. Junqueira-Junior , E. T. Dauricio , J. L. F. Azevedo

In this work, we present a novel data-based approach to turbulence modelling for Large Eddy Simulation (LES) by artificial neural networks. We define the exact closure terms including the discretization operators and generate training data…

Computational Engineering, Finance, and Science · Computer Science 2019-10-09 Andrea D. Beck , David G. Flad , Claus-Dieter Munz

A dynamical low-rank approximation is developed for reduced-order modeling (ROM) of the filtered density function (FDF) transport equation, which is utilized for large eddy simulation (LES) of turbulent reacting flows. In this methodology,…

Fluid Dynamics · Physics 2025-03-25 Aidyn Aitzhan , Peyman Givi , Hessam Babaee

The use of extended surfaces find wide range of applications in heat transfer devices for achieving heat transfer augmentation like gas turbine blade cooling and nuclear reactor core since the last few decades. So, understanding the…

Fluid Dynamics · Physics 2022-09-01 Auronil Mukherjee , Arnab Chakraborty

A low-dimensional model (LDM) for turbulent Rayleigh-Benard convection in a Cartesian cell with square domain, based on the Galerkin projection of the Boussinesq equations onto a finite set of empirical eigenfunctions, is presented. The…

Fluid Dynamics · Physics 2011-08-30 Jorge Bailon-Cuba , Joerg Schumacher

A scale-resolving simulation methodology that includes stochastic energy backscatter is incorporated into a proprietary block-structured compressible flow solver. Particular attention is devoted to the discretisation of the convective terms…

Fluid Dynamics · Physics 2025-11-12 Angelo Passariello , Pietro Catalano , Carmine De Lucia , Renato Tognaccini

As the representative of the shock-capturing scheme, the Roe scheme fails to LES because important turbulent characteristics cannot be reproduced such as the famous k-5/3 spectral law owing to large numerical dissipation. In this paper, the…

Fluid Dynamics · Physics 2016-07-26 Xue-song Li

High Reynolds Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of…

Over the last years, supervised learning (SL) has established itself as the state-of-the-art for data-driven turbulence modeling. In the SL paradigm, models are trained based on a dataset, which is typically computed a priori from a…

Fluid Dynamics · Physics 2022-12-23 Marius Kurz , Philipp Offenhäuser , Andrea Beck