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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

In large eddy simulation of atmospheric boundary layer flows over wind farms, wall-layer models are generally imposed for the surface fluxes without considering the spatial variability of the surface roughness. In this study, we consider…

Fluid Dynamics · Physics 2022-05-03 Jagdeep Singh , Jahrul Alam

Over the last two decades, both experiments and simulations have demonstrated that transverse wall oscillations with properly selected amplitude and frequency can reduce turbulent drag by as much as 40%. In this paper, we develop a…

Fluid Dynamics · Physics 2013-04-23 Rashad Moarref , Mihailo R. Jovanović

While deep learning has shown tremendous success in a wide range of domains, it remains a grand challenge to incorporate physical principles in a systematic manner to the design, training, and inference of such models. In this paper, we aim…

Computational Physics · Physics 2020-06-16 Rui Wang , Karthik Kashinath , Mustafa Mustafa , Adrian Albert , Rose Yu

Fluid turbulence is an important problem for physics and engineering. Turbulence modeling deals with the development of simplified models that can act as surrogates for representing the effects of turbulence on flow evolution. Such models…

Fluid Dynamics · Physics 2021-11-16 J P Panda

Predicting the behavior of turbulent flows using large-eddy simulation requires modeling of the subgrid-scale stress tensor. This tensor can be approximated using mixed models, which combine the dissipative nature of functional models with…

Fluid Dynamics · Physics 2021-01-11 L. B. Streher , M. H. Silvis , P. Cifani , R. W. C. P. Verstappen

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy…

Fluid Dynamics · Physics 2025-12-01 Eduardo Vital , Jean-Marc Gratien , Yassine Ayoun , Thibault Faney , Julien Bohbot

Complex turbulent flow simulations are an integral aspect of the engineering design process. The mainstay of these simulations is represented by eddy viscosity based turbulence models. Eddy viscosity models are computationally cheap due to…

Fluid Dynamics · Physics 2024-08-14 Minghan Chu , Weicheng Qian

We study the numerical errors of large-eddy simulation (LES) in isotropic and wall-bounded turbulence. A direct-numerical-simulation (DNS)-aided LES formulation, where the subgrid-scale (SGS) term of the LES is computed by using filtered…

Fluid Dynamics · Physics 2022-08-05 H. Jane Bae , Adrian Lozano-Duran

The rational large eddy simulation (RLES) model is applied to turbulent channel flows. This approximate deconvolution model is based on a rational (subdiagonal Pade') approximation of the Fourier transform of the Gaussian filter and is…

Numerical Analysis · Mathematics 2025-10-20 T. Iliescu , P. Fischer

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

We conducted WMLES to examine the performance of a simple and widely used ODE-based equilibrium wall model in a spatially-developing 3D TBL inside a bent square duct (Schwarz and Bradshaw 1994) and 3D separated flows behind a skewed bump…

Fluid Dynamics · Physics 2020-01-07 Minjeong Cho , George I. Park , Adrián Lozano-Durán , Parviz Moin

To validate the second-by-second dynamics of turbines in field experiments, it is necessary to accurately reconstruct the winds going into the turbine. Current time-resolved inflow reconstruction techniques estimate wind behavior in…

A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in…

Fluid Dynamics · Physics 2023-07-19 Justin Sirignano , Jonathan F. MacArt

A shear-improved Smagorinsky model is introduced based on recent results concerning shear effects in wall-bounded turbulence by Toschi et al. (2000). The Smagorinsky eddy-viscosity is modified subtracting the magnitude of the mean shear…

Chaotic Dynamics · Physics 2015-06-26 E. Leveque , F. Toschi , L. Shao , J. -P. Bertoglio

We investigate statistics of large-scale structures from large-eddy simulation (LES) of turbulent channel flow at friction Reynolds numbers $Re_\tau = 2 {\rm k}$ and $200 {\rm k}$. To properly capture the behaviour of large-scale…

Fluid Dynamics · Physics 2015-05-18 D. Chung , B. J. McKeon

Wall-modeled large-eddy simulations (WMLES) are conducted for the flow over the Sandia Axisymmetric Transonic Bump (ATB) at bump chord Reynolds number, Re = 1x10^6 and Mach number, Ma = 0.875. Utilizing various subgrid-scale and wall…

Fluid Dynamics · Physics 2023-05-11 Rahul Agrawal , Ahmed Elnahhas , Parviz Moin

Wall-models are essential for enabling large-eddy simulations (LESs) of realistic problems at high Reynolds numbers. The present study is focused on approaches that directly model the wall shear stress, specifically on filling the gap…

Fluid Dynamics · Physics 2015-12-01 Stefan Hickel , Emile Touber , Julien Bodart , Johan Larsson

The hybrid wall-modeled large-eddy simulation (WMLES) and immersed boundary (IB) method offers significant flexibility for simulating high Reynolds number flows involving complex boundaries. However, the approximate boundary conditions…

Fluid Dynamics · Physics 2025-06-30 Zhideng Zhou , Fengshun Zhang , Xiaolei Yang

In this paper, a turbulence model based on deep neural network is developed for turbulent flow around airfoil at high Reynolds numbers. According to the data got from the Spalart-Allmaras (SA) turbulence model, we build a neural network…

Fluid Dynamics · Physics 2021-11-29 Xuxiang Sun , Wenbo Cao , Yilang Liu , Linyang Zhu , Weiwei Zhang