English
Related papers

Related papers: LES-informed resolvent-based estimation of turbule…

200 papers

We consider linear feedback flow control of the largest scales in an incompressible turbulent channel flow at a friction Reynolds number of Re$_{\tau}$ = 2000. A linear model is formed by linearizing the Navier-Stokes equations about the…

Fluid Dynamics · Physics 2020-10-20 Stephan F. Oehler , Simon J. Illingworth

Deep reinforcement learning (DRL) is employed to develop control strategies for drag reduction in direct numerical simulations (DNS) of turbulent channel flows at high Reynolds numbers. The DRL agent uses near-wall streamwise velocity…

Fluid Dynamics · Physics 2025-03-19 Zisong Zhou , Mengqi Zhang , Xiaojue Zhu

Resolvent analysis is a powerful tool that can reveal the linear amplification mechanisms between the forcing inputs and the response outputs about a base flow. These mechanisms can be revealed in terms of a pair of forcing and response…

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

The pressure strain correlation plays a critical role in the Reynolds stress transport modelling. Accurate modelling of the pressure strain correlation leads to proper prediction of turbulence stresses and subsequently the other terms of…

Fluid Dynamics · Physics 2021-03-02 J P Panda , H V Warrior

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

Direct numerical simulations (DNS) stand out as formidable tools in studying turbulent flows. Despite the fact that the achievable Reynolds number remains lower than those available through experimental methods, DNS offers a distinct…

Fluid Dynamics · Physics 2024-06-06 Sergio Hoyas , Ricardo Vinuesa , Peter Schmid , Hassan Nagib

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

Fluid Dynamics · Physics 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

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…

The large structures in the outer layer of turbulent wall flows are of great physical importance, because they contain a substantial fraction of the streamwise kinetic energy and of the Reynolds stresses. Nevertheless, the organization of…

Fluid Dynamics · Physics 2013-09-12 Juan C. del Alamo , Javier Jimenez

Invariant solutions of the Navier-Stokes equations play an important role in the spatiotemporally chaotic dynamics of turbulent shear flows. Despite the significance of these solutions, their identification remains a computational…

Fluid Dynamics · Physics 2023-10-11 Omid Ashtari , Tobias M. Schneider

In the current study, model expressions for fifth-order velocity moments obtained from the truncated Gram-Charlier series expansions model for a turbulent flow field probability density function are validated using data from direct…

Fluid Dynamics · Physics 2021-02-24 S. V. Poroseva , S. M. Murman

Spatially developing round jet flows are fundamental to numerous engineering applications. This letter applies the wave-particle turbulence simulation (WPTS) method, a recently developed multiscale approach, to simulate a spatially…

Fluid Dynamics · Physics 2025-07-22 Xiaojian Yang , Kun Xu

The stratified inclined duct (SID) flow provides a canonical model for sustained, buoyancy-driven exchange between two reservoirs of different density, and emerges as a new paradigm in geophysical fluid dynamics. Yet, the flow dynamics…

Fluid Dynamics · Physics 2026-03-18 Rundong Zhou , Adrien Lefauve , Roberto Verzicco , Detlef Lohse

The prediction of aircraft aerodynamic quantities of interest remains among the most pressing challenges for computational fluid dynamics. The aircraft aerodynamics are inherently turbulent with mean-flow three-dimensionality, often…

Fluid Dynamics · Physics 2021-05-25 Adrián Lozano-Durán , Hyunji Jane Bae

Starting with an integral formulation of mass flow rate through an ensemble of isotherms constituting a statistically planar, turbulent premixed flame, a scaling for the corresponding turbulent flame speed is derived without invoking…

Fluid Dynamics · Physics 2022-07-14 Swetaprovo Chaudhuri , Bruno Savard

We introduce a widely applicable tensor network-based framework for developing reduced order models describing wall-bounded fluid flows. As a paradigmatic example, we consider the incompressible Navier-Stokes equations and the lid-driven…

Fluid Dynamics · Physics 2024-10-10 Martin Kiffner , Dieter Jaksch

Wall modelling in large-eddy simulation (LES) is necessary to overcome the prohibitive near-wall resolution requirements in high-Reynolds-number turbulent flows. Most existing wall models rely on assumptions about the state of the boundary…

Fluid Dynamics · Physics 2021-10-26 H. Jane Bae , Adrián Lozano-Durán , Sanjeeb T. Bose , Parviz Moin

Flow past a high-lift low-pressure turbine (LPT) blade in a cascade could be quite complex as phenomena like separation and transition are often involved. For a highly loadedT106A blade at a high incidence and relatively low Reynolds…

Fluid Dynamics · Physics 2020-04-24 Rajesh Ranjan , S. M. Deshpande , Roddam Narasimha

While direct numerical simulations (DNS) are the most accurate method for studying turbulence, their large computational cost restricts their use to idealized configurations and to Reynolds numbers well below those found in practical…

Fluid Dynamics · Physics 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko
‹ Prev 1 4 5 6 7 8 10 Next ›