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For high-fidelity predictions of turbulent flows in complex practical engineering problems, the Wall-Modeled (WM) Large-Eddy Simulation (LES) has aroused great interest. In the present study, we prove that the conventional Wall-Stress…

Fluid Dynamics · Physics 2025-11-12 Mohammad Taghvaei , Ehsan Amani

Turbulent problems in industrial applications are predominantly solved using Reynolds Averaged Navier Stokes (RANS) turbulence models. The accuracy of the RANS models is limited due to closure assumptions that induce uncertainty into the…

Fluid Dynamics · Physics 2018-02-20 Atieh Alizadeh Moghaddam , Amir Sadaghiyani

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

A previously developed modeling procedure for large eddy simulations (LESs) is extended to allow physical space implementations for inhomogeneous flows. The method is inspired by the well-established theoretical analyses and numerical…

Fluid Dynamics · Physics 2022-10-28 Guangrui Sun , J. Andrzej Domaradzki

Direct numerical simulation (DNS) is very accurate however, the computational cost increases significantly with the increase in Reynolds number. On the other hand, we have the Reynolds Averaged Navier Stokes (RANS) method for simulating…

Fluid Dynamics · Physics 2023-01-12 Manthan Mahajan , Nitin Kumar , Deep Shikha , Vamsi K Chalamalla , Sawan S Sinha

We show that in addition to providing effective and competitive closures, when analysed in terms of dynamics and physically-relevant diagnostics, artificial neural networks (ANNs) can be both interpretable and provide useful insights in the…

Computational Physics · Physics 2020-12-30 Gavin D. Portwood , Balasubramanya T. Nadiga , Juan A. Saenz , Daniel Livescu

Large-eddy simulations (LES) are widely-used for computing high Reynolds number turbulent flows. Spatial filtering theory for LES is not without its shortcomings, including how to define filtering for wall-bounded flows, commutation errors…

Fluid Dynamics · Physics 2022-02-02 Perry L. Johnson

We present results of implicit large eddy simulation (LES) and different Reynolds-averaged Navier-Stokes (RANS) models of the MTU 161 low pressure turbine at an exit Reynolds number of 90,000 and exit Mach number of 0.6. The LES results are…

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

The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant times and length scales. However, due to the dissipative nature of the Navier-Stokes equations, the long-term dynamics are expected to lie on a…

Fluid Dynamics · Physics 2025-10-15 C. Ricardo Constante-Amores , Alec J. Linot , Michael D. Graham

The shock induced mixing of two gases separated by a perturbed interface is investigated through Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). In a simulation, physical dissipation of the velocity field and species mass…

Fluid Dynamics · Physics 2015-06-18 Britton J. Olson , Jeffrey A. Greenough

In this paper, deep learning (DL) methods are evaluated in the context of turbulent flows. Various generative adversarial networks (GANs) are discussed with respect to their suitability for understanding and modeling turbulence. Wasserstein…

Fluid Dynamics · Physics 2022-10-31 Mathis Bode , Michael Gauding , Jens Henrik Göbbert , Baohao Liao , Jenia Jitsev , Heinz Pitsch

Large-eddy simulation of incompressible turbulent flow has been extensively investigated; hence, a variety of models suited for different numerical schemes have been developed. In the case of compressible flow, the modeling is more…

Fluid Dynamics · Physics 2020-07-15 Ahmad Peyvan , Zia Ghiasi , Dongru Li , Jonathan Komperda , Farzad Mashayek

A numerical study for a hydrogen (H2) jet in an air crossflow (JICF) was performed using direct numerical simulation (DNS), large eddy simulation (LES), and Reynolds-averaged Navier-Stokes (RANS) approaches, based on a geometry…

Deep learning (DL) has recently emerged as a candidate for closure modeling of large-eddy simulation (LES) of turbulent flows. High-fidelity training data is typically limited: it is computationally costly (or even impossible) to…

Fluid Dynamics · Physics 2023-03-07 Justin Sirignano , Jonathan F. MacArt

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

In many engineering and industrial applications, the investigation of rotating turbulent flow is of great interest. In rotor-stator cavities, the centrifugal and Coriolis forces have a strong influence on the turbulence by producing a…

We carry out direct numerical simulation (DNS) of flow in a turbulent square duct by focusing on heat transfer effects, considering the case of unit Prandtl number. Reynolds numbers up to $Re_\tau \approx 2000$ are considered which are much…

Fluid Dynamics · Physics 2022-05-11 Davide Modesti , Sergio Pirozzoli

An adjoint-based variational optimal mixed model (VOMM) is proposed for subgrid-scale (SGS) closure in large-eddy simulation (LES) of turbulence. The stabilized adjoint LES equations are formulated by introducing a minimal regularization to…

Fluid Dynamics · Physics 2023-07-19 Zelong Yuan , Yunpeng Wang , Xiaoning Wang , Jianchun Wang

Reynolds-Averaged Navier-Stokes(RANS) method will still play a vital role in the following several decade in aerospace engineering. Although RANS models are widely used, empiricism and large discrepancies between models reduce the…

Fluid Dynamics · Physics 2018-07-05 Weiwei Zhang , Linyang Zhu , Yilang Liu , Jiaqing Kou
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