English
Related papers

Related papers: Hidden mechanism of dynamic large-eddy simulation …

200 papers

We developed a novel autonomously dynamic nonlocal turbulence model for the large and very large eddy simulation (LES, VLES) of the homogeneous isotropic turbulent flows (HIT). The model is based on a generalized (integer-to-noninteger)…

Fluid Dynamics · Physics 2022-03-07 S. Hadi Seyedi , Mohsen Zayernouri

Model reduction is a key technology for large-scale physical systems in science and engineering, as it brings behavior expressed in many degrees of freedom to a more manageable size that subsequently allows control, optimization, and…

Fluid Dynamics · Physics 2024-12-31 R. Ayoub , M. Oulghelou , P. J Schmid

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of subgrid scale modeling for unsteady turbulent jet flows as a preliminary step…

Fluid Dynamics · Physics 2023-01-03 Carlos Junqueira-Junior , Sami Yamouni , Joao Luiz F. Azevedo , William Wolf

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 a wall model for large-eddy simulation that incorporates surface-roughness effects and is applicable across low- and high-speed flows, for both transitional and fully rough conditions. The model, implemented using an artificial…

Fluid Dynamics · Physics 2026-01-29 Rong Ma , Adrian Lozano-Duran

We present a high-order implicit large-eddy simulation (ILES) approach for simulating transitional turbulent flows. The approach consists of an Interior Embedded Discontinuous Galerkin (IEDG) method for the discretization of the…

Fluid Dynamics · Physics 2016-05-04 Pablo Fernandez , Ngoc-Cuong Nguyen , Xevi Roca , Jaime Peraire

High-order Discontinuous Galerkin (DG) methods offer excellent accuracy for turbulent flow simulations, especially when implemented on GPU-oriented architectures that favor very high polynomial orders. On modern GPUs, high-order polynomial…

We put forth a dynamic modeling framework for sub-grid parametrization of large eddy simulation of turbulent flows based upon the use of the approximate deconvolution procedure to compute the Smagorinsky constant self-adaptively from the…

Fluid Dynamics · Physics 2016-05-02 Romit Maulik , Omer San

The development of a wall model using machine learning methods for the large-eddy simulation (LES) of separated flows is still an unsolved problem. Our approach is to leverage the significance of separated flow data, for which existing…

Fluid Dynamics · Physics 2024-12-25 Zhideng Zhou , Xin-lei Zhang , Guo-wei He , Xiaolei Yang

Stochastic differential equations (SDEs) are a staple of mathematical modelling of temporal dynamics. However, a fundamental limitation has been that such models have typically been relatively inflexible, which recent work introducing…

Machine Learning · Computer Science 2021-05-12 Patrick Kidger , James Foster , Xuechen Li , Harald Oberhauser , Terry Lyons

In large-eddy simulations, subgrid-scale (SGS) processes are parameterized as a function of filtered grid-scale variables. First-order, algebraic SGS models are based on the eddy-viscosity assumption, which does not always hold for…

Filtered budgets for anelastic turbulence and a general expression of the turbulent sensible heat flux are derived for a multicomponent fluid with an arbitrary equation of state. A family of subgrid-scale closures is then found under the…

Fluid Dynamics · Physics 2026-01-26 Thomas Dubos

In large-eddy simulations of atmospheric boundary layer turbulence, the lumped coefficient in the eddy-diffusion subgrid-scale (SGS) model is known to depend on scale for the case of inert scalars. This scale dependence is predominant near…

Atmospheric and Oceanic Physics · Physics 2016-08-16 Jean-François Vinuesa , Fernando Porté-Agel , Sukanta Basu , Rob Stoll

System inference for nonlinear dynamic models, represented by ordinary differential equations (ODEs), remains a significant challenge in many fields, particularly when the data are noisy, sparse, or partially observable. In this paper, we…

Machine Learning · Computer Science 2025-12-25 Hyunwoo Cho , Hyeontae Jo , Hyung Ju Hwang

We present a new approach for constructing data-driven subgrid stress models for large eddy simulation of turbulent flows using anisotropic grids. The key to our approach is a Galilean, rotationally, reflectionally and unit invariant model…

Fluid Dynamics · Physics 2023-07-18 Aviral Prakash , Kenneth E. Jansen , John A. Evans

Assuming a general constitutive relation for the turbulent stresses in terms of the local large-scale velocity gradient, we constructed a class of subgrid-scale models for large-eddy simulation that are consistent with important physical…

Fluid Dynamics · Physics 2015-10-28 Maurits H. Silvis , Roel Verstappen

Large eddy simulation (LES) has become a central technique for simulating turbulent flows in engineering and applied sciences, offering a compromise between accuracy and computational cost by resolving large scale motions and modeling the…

Fluid Dynamics · Physics 2025-08-27 Rik Hoekstra , Wouter Edeling

We formulate and implement the Euler equations with SGS dynamics and provide numerical tests of an SGS turbulence energy model that predicts the turbulent pressure of unresolved velocity fluctuations and the rate of dissipation for highly…

Astrophysics of Galaxies · Physics 2015-05-20 W. Schmidt , C. Federrath

One of the greatest challenges to using large-eddy simulations (LES) in engineering applications is the large number of grid points required near walls. To mitigate this issue, researchers often couple LES with a simplified model of the…

Fluid Dynamics · Physics 2016-11-15 Alexandre Marques , Qiqi Wang , Johan Larsson , Gregory Laskowski , Sanjeeb Bose

Identifying dynamical system (DS) is a vital task in science and engineering. Traditional methods require numerous calls to the DS solver, rendering likelihood-based or least-squares inference frameworks impractical. For efficient parameter…

Computation · Statistics 2024-09-19 Ying Zhou , Jinglai Li , Xiang Zhou , Hongqiao Wang