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Large-eddy simulation (LES) of a turbulent flow through an array of building-like obstacles is an idealized model to study transport of contaminants in the urban atmospheric boundary layer (UABL). A reasonably accurate LES prediction of…

Fluid Dynamics · Physics 2017-11-09 Jahrul M Alam , Luke P. J. Fitzpatrick

Non-equilibrium wall turbulence with mean-flow three-dimensionality is ubiquitous in geophysical and engineering flows. Under these conditions, turbulence may experience a counter-intuitive depletion of the turbulent stresses, which has…

Fluid Dynamics · Physics 2020-01-08 Adrián Lozano-Durán , Marco Giometto , George I. Park , Parviz Moin

In the last decade, progresses in additive manufacturing (AM) have paved the way for optimized heat exchangers, whose disruptive design will depend on predictive numerical simulations. Typical AM rough surfaces show limited resemblance to…

Fluid Dynamics · Physics 2023-05-10 Himani Garg , Lei Wang , Guillaume Sahut , Christer Fureby

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

Fluid Dynamics · Physics 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem

In wall-modeled large-eddy simulations (WMLES), the near-wall model plays a significant role in predicting the skin friction, although the majority of the boundary layer is resolved by the outer large-eddy simulation (LES) solver. In this…

Fluid Dynamics · Physics 2020-10-09 Kevin Patrick Griffin , Lin Fu

We study the error scaling properties of large-eddy simulation (LES) in the outer region of wall-bounded turbulence at moderately high Reynolds numbers. In order to avoid the additional complexity of wall-modeling, we perform LES of…

Fluid Dynamics · Physics 2021-10-26 Adrián Lozano-Durán , Hyunji Jane Bae

We present a framework for Large Eddy Simulations (LES) with Immersed Boundaries (IBs) to simulate high Reynolds number flows over complex walls. In this approach, which we call Immersed Boundary-Modeled LES (IBMLES), we volume-filter the…

Fluid Dynamics · Physics 2025-11-03 Morrison Rickard , M. Houssem Kasbaoui

Turbulent flow across an in-line array of tube-banks with transverse and longitudinal pitch PT /D = 2.67, and PL /D = 2.31, has been simulated successfully by Large Eddy Simulation (LES) based on the dynamic Smagorinsky subgrid scale model…

Fluid Dynamics · Physics 2016-05-30 C. Jin , I. Potts , D. C. Swailes , M. W. Reeks

Turbulent flows are fundamental in engineering and the environment, but their chaotic and three-dimensional (3-D) nature makes them computationally expensive to simulate. In this work, a dimensionality reduction technique is investigated to…

Fluid Dynamics · Physics 2020-12-16 Bernat Font

We present a new approach for constructing data-driven subgrid stress models for large eddy simulation of turbulent flows. The key to our approach is representation of model input and output tensors in the filtered strain rate eigenframe.…

Fluid Dynamics · Physics 2022-08-24 Aviral Prakash , Kenneth E. Jansen , John A. Evans

Data from direct numerical simulations of turbulent flows are commonly used to train neural network-based models as subgrid closures for large-eddy simulations; however, models with low a priori accuracy have been observed to fortuitously…

Fluid Dynamics · Physics 2024-09-02 Mark Benjamin , Gianluca Iaccarino

This work presents a review and perspectives on recent developments in the use of machine learning (ML) to augment Reynolds-averaged Navier--Stokes (RANS) and Large Eddy Simulation (LES) models of turbulent flows. Different approaches of…

Fluid Dynamics · Physics 2021-05-19 Karthik Duraisamy

First principle based prediction of mean flow quantities of wall-bounded turbulent flows (channel, pipe, and turbulent boundary layer - TBL) is of great importance from both physics and engineering standpoints. Here (Part I), we present a…

Fluid Dynamics · Physics 2015-05-12 Zhen-Su She , Xi Chen , Fazle Hussain

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

Turbulent flows play an important role in many scientific and technological design problems. Both Sub-Grid Scale (SGS) models in Large Eddy Simulations (LES) and Reynolds Averaged Navier Stokes (RANS) based modeling will require turbulence…

Fluid Dynamics · Physics 2024-07-16 Minghan Chu

Large Eddy Simulation (LES) with dynamic sub-grid scale eddy viscosity model has been applied to numerically investigate the evolution of complicated flow structures in supersonic base flow with mass bleed. Mean flow properties obtained…

Fluid Dynamics · Physics 2021-02-15 Pratik Das , Ashoke De

We introduce a new Large Eddy Simulation model in a channel, based on the projection on finite element spaces as filtering operation in its variational form, for a given triangulation $\{{\cal T}_h \}_{h>0}$. The eddy viscosity is expressed…

Mathematical Physics · Physics 2013-02-13 Tomas Chacon Rebello , Roger Lewandowski

In this paper the capabilities of the turbulence-resolving Eulerian-Eulerian two-phase flow model to predict the suspension of mono-dispersed finite-sized solid particles in a boundary layer flow are investigated. For heavier-than-fluid…

Fluid Dynamics · Physics 2021-03-08 Antoine Mathieu , Julien Chauchat , Cyrille Bonamy , Guillaume Balarac , Tian-Jian Hsu

In the field of Large Eddy Simulation, the Smagorinsky subgrid scale model (in some form) is the most commonly accepted and used subgrid scale model. The purpose of this paper is to address the main weakness of the Smagorinsky model, its…

Numerical Analysis · Mathematics 2025-10-20 Tommy Kunhung Kim

We demonstrate several techniques to encourage practical uses of neural networks for fluid flow estimation. In the present paper, three perspectives which are remaining challenges for applications of machine learning to fluid dynamics are…

Fluid Dynamics · Physics 2022-05-19 Masaki Morimoto , Kai Fukami , Kai Zhang , Koji Fukagata