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A machine learning method to predict steady external fluid flows using elliptic input features is introduced. Using data from as few as one high-fidelity simulation, the proposed method produces models generalizable under changes to…

We present wall-resolved large-eddy simulations (LES) of the incompressible Navier-Stokes equations together with empirical modeling for {turbulent} Taylor-Couette {(TC)} flow where the inner cylinder is rotating with angular velocity…

Fluid Dynamics · Physics 2019-08-20 Wan Cheng , Dale I. Pullin , Ravi Samtaney

The objective of this study is to assess the capability of convolution-based neural networks to predict wall quantities in a turbulent open channel flow. The first tests are performed by training a fully-convolutional network (FCN) to…

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…

Fluid Dynamics · Physics 2019-05-31 Anikesh Pal

We investigate the role of the bulk eddy-viscosity variation on the well-known log-layer mismatch problem. An analysis of the mean momentum-balance shows that the modeled stress term close to the wall can dominate because of the bulk…

Fluid Dynamics · Physics 2017-12-22 Rey DeLeon , Inanc Senocak

This study explores the integration of machine learning (ML) techniques with large eddy simulation (LES) for predicting species mass fraction and flame characteristics in partially premixed turbulent jet flames. The LES simulations,…

Fluid Dynamics · Physics 2025-05-05 Amirali Shateri , Zhiyin Yang , Jianfei Xie

A large eddy simulation (LES) with an extended Smagorinsky model has been carried to investigate numerically the fully developed turbulent flow of a shear thinning fluid (n=0.75) in a stationary pipe at a simulation's Reynolds number equals…

Fluid Dynamics · Physics 2020-06-01 Mohamed Abdi , Meryem Ould-Rouiss , Abdelkader Noureddine

We study the sensitivity of wall model input variables to the modeling choices of the outer LES. This work is motivated by sensitivities observed in dynamic slip wall models. These dynamic wall models use variables from the near-wall LES…

Fluid Dynamics · Physics 2022-02-10 Michael Whitmore , Adrián Lozano-Durán , Parviz Moin

Predictions of the spatial representation of instantaneous wall-bounded flows, via coherent structure-based models, are highly sensitive to the geometry of the representative structures employed by them. In this study, we propose a…

Fluid Dynamics · Physics 2024-04-30 Rahul Deshpande , Charitha M. de Silva , Myoungkyu Lee , Jason P. Monty , Ivan Marusic

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of subgrid scale modeling for unsteady turbulent jet flows as a preliminary step…

Fluid Dynamics · Physics 2023-01-03 Carlos Junqueira-Junior , Sami Yamouni , Joao Luiz F. Azevedo , William Wolf

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)…

Fluid Dynamics · Physics 2026-04-13 Ben-Rui Xu , Ao Xu

There is wide agreement that the accuracy of turbulence models suffer from their sensitivity with respect to physical input data, the uncertainties of user-elected parameters, as well as the model inadequacy. However, the application of…

Numerical Analysis · Mathematics 2015-08-07 Hoang A. Tran , Clayton G. Webster , Guannan Zhang

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

We continue a previous work in which {\em a priori} estimates were derived on subgrid stress and subgrid flux for filtering schemes used in the turbulence modelling method of Large-Eddy Simulation (LES). The estimates were derived there as…

chao-dyn · Physics 2008-02-03 Gregory L. Eyink

In this study, ensembles of experimental data are presented and utilized to compare and validate two models used in the simulation of variable density, compressible turbulent mixing. Though models of this kind (Reynolds Averaged Navier…

Fluid Dynamics · Physics 2022-03-07 Benjamin Musci , Britton Olson , Samuel Petter , Gokul Pathikonda , Devesh Ranjan

Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. As a first step towards a data-driven wall-model, a…

The majority of practical flows, particularly those flows in applications of importance to transport, distribution and climate, are turbulent and as a result experience complex three-dimensional motion with increased drag compared with the…

Fluid Dynamics · Physics 2015-03-17 B. J. McKeon , A. S. Sharma , I. Jacobi

The simulation of high Reynolds number (Re) separated turbulent flows faces significant problems for decades: large eddy simulation (LES) is computationally too expensive, and Reynolds-averaged Navier-Stokes (RANS) methods and hybrid…

Fluid Dynamics · Physics 2024-12-02 Stefan Heinz , Adeyemi Fagbade

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…

Atmospheric and Oceanic Physics · Physics 2016-08-16 Sukanta Basu , Fernando Porté-Agel

We develop a one-dimensional network model to predict the steady-state distribution of yield-stress fluids in branched pipe manifolds under wall-slip conditions. The model accounts for major friction losses between junctions and…

Fluid Dynamics · Physics 2025-11-18 Elliott Sutton , Waldo Rosales Trujillo , Adam Kowalski , Cláudio P. Fonte , Anne Juel