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The construction of discontinuous Galerkin (DG) methods for the compressible Euler or Navier-Stokes equations (NSE) includes the approximation of non-linear flux terms in the volume integrals. The terms can lead to aliasing and stability…

Numerical Analysis · Mathematics 2020-08-26 Nico Krais , Gero Schnücke , Thomas Bolemann , Gregor Gassner

We present a numerical method for Large Eddy Simulations (LES) of compressible two-phase flows. The method is validated for the flow in a micro channel with a step-like restriction. This setup is representative for typical cavitating…

Fluid Dynamics · Physics 2014-01-28 S Hickel , M. Mihatsch , S. J. Schmidt

We develop a $ P $-multigrid solver to simulate locally preconditioned unsteady compressible Navier-Stokes equations at low Mach numbers with implicit high-order methods. Specifically, the high-order flux reconstruction/correction procedure…

Computational Physics · Physics 2019-08-13 Lai Wang , Meilin Yu

The present paper addresses the numerical solution of turbulent flows with high-order discontinuous Galerkin methods for discretizing the incompressible Navier-Stokes equations. The efficiency of high-order methods when applied to…

Fluid Dynamics · Physics 2018-08-29 Niklas Fehn , Wolfgang A. Wall , Martin Kronbichler

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

Mathematical regularisation of the nonlinear terms in the Navier-Stokes equations provides a systematic approach to deriving subgrid closures for numerical simulations of turbulent flow. By construction, these subgrid closures imply…

Chaotic Dynamics · Physics 2009-11-11 Bernard J. Geurts , Darryl D. Holm

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of unsteady turbulent jet flows for aeroacoustic analyses of main engine rocket…

Fluid Dynamics · Physics 2022-12-26 Carlos Junqueira-Junior , Sami Yamouni , Joao Luiz F. Azevedo , William Wolf

We consider a Leray model with a nonlinear differential low-pass filter for the simulation of incompressible fluid flow at moderately large Reynolds number (in the range of a few thousands) with under-refined meshes. For the implementation…

Numerical Analysis · Mathematics 2024-12-20 Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

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…

Scale-resolving simulations of high Reynolds number incompressible flows are often limited by the Courant-Friedrichs-Lewy (CFL) stability restriction imposed by explicit time-stepping schemes, resulting in small time step sizes and long…

Fluid Dynamics · Physics 2026-04-20 Henrik Wüstenberg , Alexandra Liosi , Spencer J. Sherwin , Joaquim Peiró , David Moxey

This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by…

Computational Engineering, Finance, and Science · Computer Science 2018-02-14 Jean-Baptiste Chapelier , Bono Wasistho , Carlo Scalo

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

In this work, we perform an aposteriori error analysis on implicit and explicit large eddy simulation closure models for solving the Burgers turbulence problem. Our closure modeling efforts include both functional and structural models…

Fluid Dynamics · Physics 2018-01-29 Romit Maulik , Omer San

The predictive accuracy of wall-modeled large eddy simulation is studied by systematic simulation campaigns of turbulent channel flow. The effect of wall model, grid resolution and anisotropy, numerical convective scheme and subgrid-scale…

Fluid Dynamics · Physics 2019-04-01 Saleh Rezaeiravesh , Timofey Mukha , Mattias Liefvendahl

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

Fluid Dynamics · Physics 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

An online Data Assimilation strategy based on the Ensemble Kalman Filter (EnKF) is used to improve the predictive capabilities of Large Eddy Simulation (LES) for the analysis of the turbulent flow in a plane channel, $Re_\tau \approx 550$.…

Fluid Dynamics · Physics 2023-10-30 Lucas Villanueva , Karine Truffin , Marcello Meldi

Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models for systems with known invariance properties. However,…

High order schemes are known to be unstable in the presence of shock discontinuities or under-resolved solution features for nonlinear conservation laws. Entropy stable schemes address this instability by ensuring that physically relevant…

Numerical Analysis · Mathematics 2024-01-12 Jesse Chan , Khemraj Shukla , Xinhui Wu , Ruofeng Liu , Prani Nalluri

One promising decomposition of turbulent dynamics is that into building blocks such as equilibrium and periodic solutions and orbits connecting these. While the numerical approximation of such building blocks is feasible for flows in small…

Fluid Dynamics · Physics 2018-11-14 Lennaert van Veen , Genta Kawahara , Tatsuya Yasuda

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
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