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In this article, we utilize machine learning to dynamically determine if a point on the computational grid requires implicit numerical dissipation for large eddy simulation (LES). The decision making process is learnt through \emph{a…

Fluid Dynamics · Physics 2019-02-07 Romit Maulik , Omer San , Jamey D Jacob

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

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

We present a framework based on the generalized lattice-Boltzmann equation using multiple relaxation times with forcing term for eddy capturing simulation of wall bounded turbulent flows. Due to its flexibility in using disparate relaxation…

Computational Physics · Physics 2009-11-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We demonstrate that an…

Fluid Dynamics · Physics 2018-12-10 Romit Maulik , Omer San , Adil Rasheed , Prakash Vedula

We investigate turbulence generated by cosmological structure formation by means of large eddy simulations using adaptive mesh refinement. In contrast to the widely used implicit large eddy simulations, which resolve a limited range of…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 W. Schmidt , A. S. Almgren , H. Braun , J. F. Engels , J. C. Niemeyer , J. Schulz , R. R. Mekuria , A. J. Aspden , J. B. Bell

This study proposes a novel method for developing discretization-consistent closure schemes for implicitly filtered Large Eddy Simulation (LES). Here, the induced filter kernel, and thus the closure terms, are determined by the properties…

Fluid Dynamics · Physics 2023-12-14 Andrea Beck , Marius Kurz

A multi-scale model for the evolution of the velocity gradient tensor in fully developed turbulence is proposed. The model is based on a coupling between a ``Restricted Euler'' dynamics [{\it P. Vieillefosse, Physica A, {\bf 14}, 150…

Chaotic Dynamics · Physics 2007-06-13 Luca Biferale , Laurent Chevillard , Charles Meneveau , Federico Toschi

In this paper, we apply a specifically designed dissipative spatial filter as sub-grid scale model within the increasingly popular discontinuous Galerkin methods and the closely related flux reconstruction high order methods for large eddy…

Computational Engineering, Finance, and Science · Computer Science 2020-02-19 David G Flad , Andrea D Beck , Philipp Guthke

This is the second part to our companion paper. The novel method to quantify artificial dissipation proposed in Part 1 is further applied in turbulent channel flow at $\mathrm{Re_\tau}=180$ using various subgrid-scale models, with an…

Fluid Dynamics · Physics 2025-03-03 Jing Sun , Roel Verstappen

Large Eddy Simulation (LES) is a very useful tool when simulating turbulent flows if we are only interested in its "larger" scales. One of the possible ways to derive the LES equations is to apply a filter operator to the Navier-Stokes…

Analysis of PDEs · Mathematics 2017-03-14 José M. Rodríguez , Raquel Taboada-Vázquez

To date no satisfying model exists to explain the mean velocity profile within the whole turbulent layer of canonical wall bounded flows. We propose a modification of the velocity profile expression that ensues from a recently proposed…

Fluid Dynamics · Physics 2018-12-10 Benoit Pinier , Etienne Mémin , Sylvain Laizet , Roger Lewandowski

We have adapted the anelastic spectral code of Barranco & Marcus (2006) to simulate a turbulent convective layer with the intention of studying the effectiveness of turbulent eddies in dissipating external shear (e.g. tides). We derive the…

Astrophysics · Physics 2015-05-13 Kaloyan Penev , Joseph Barranco , Dimitar Sasselov

A phenomenological two-fluid model of the (time-reversible) spectrally-truncated 3D Euler equation is proposed. The thermalized small scales are first shown to be quasi-normal. The effective viscosity and thermal diffusion are then…

Fluid Dynamics · Physics 2009-11-13 Giorgio Krstulovic , Marc-Etienne Brachet

We model a 3D turbulent fluid, evolving toward a statistical equilibrium, by adding to the equations for the mean field $(v, p)$ a term like $-\alpha \nabla\cdot(\ell(x) D v_t)$. This is of the Kelvin-Voigt form, where the Prandtl mixing…

Analysis of PDEs · Mathematics 2019-07-23 Cherif Amrouche , Luigi C. Berselli , Roger Lewandowski , Dinh Duong Nguyen

This study presents a hybrid reduced-order modeling (ROM) framework for turbulent incompressible flows on collocated finite volume grids. The methodology employs the "discretize-then-project" consistent flux strategy, which ensures mass…

Numerical Analysis · Mathematics 2026-01-28 Nadim Rooholamin , Kabir Bakhshaei , Giovanni Stabile

The closure problem of turbulence is still a challenging issue in turbulence modeling. In this work, a stability condition is used to close turbulence. Specifically, we regard single-phase flow as a mixture of turbulent and non-turbulent…

Fluid Dynamics · Physics 2014-06-20 Lin Zhang , Xiaoping Qiu , Limin Wang , Jinghai Li

Recent developments in vortex particle methods for simulating three-dimensional incompressible flows are presented. A lightweight, dynamic Large-Eddy Simulation model is tested, featuring a dynamic procedure that relies solely on Lagrangian…

Fluid Dynamics · Physics 2026-01-13 Flavio A. C. Martins , Alexander van Zuijlen , Carlos J. Simao Ferreira

Data-driven turbulence modeling is experiencing a surge in interest following algorithmic and hardware developments in the data sciences. We discuss an approach using the differentiable physics paradigm that combines known physics with…

We propose a variational approach to identification of an optimal nonlinear eddy viscosity as a subscale turbulence representation for POD models. The ansatz for the eddy viscosity is given in terms of an arbitrary function of the resolved…

Fluid Dynamics · Physics 2015-06-19 Bartosz Protas , Bernd R. Noack , Jan Östh