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Large eddy simulation (LES) of turbulence in complex geometries and domains is often conducted with high aspect ratio resolution cells of varying shapes and orientations. The effects of such anisotropic resolution are often simplified or…

Fluid Dynamics · Physics 2019-11-20 Sigfried Haering , Myoungkyu Lee , Robert D. Moser

The problem of an accurate Eulerian-Lagrangian modeling of inertial particle dispersion in Large Eddy Simulation (LES) of turbulent wall-bounded flows is addressed. We run Direct Numerical Simulation (DNS) for turbulent channel flow at…

Fluid Dynamics · Physics 2009-11-13 C. Marchioli , M. V. Salvetti , A. Soldati

New implicit and implicit-explicit time-stepping methods for the wave equation in second-order form are described with application to two and three-dimensional problems discretized on overset grids. The implicit schemes are single step,…

Numerical Analysis · Mathematics 2024-04-24 Allison M. Carson , Jeffrey W. Banks , William D. Henshaw , Donald W. Schwendeman

In this paper implicit and explicit exact difference schemes (EDS) for system $\textbf{x}' = A\textbf{x}$ of three linear differential equations with constant coefficients are constructed. Numerical simulations for stiff problem and for…

Numerical Analysis · Mathematics 2017-02-03 Quang A Dang , Manh Tuan Hoang

Large-Eddy Simulations (LES) of two-phase turbulent flows exhibit quantitative differences in particle statistics if compared to Direct Numerical Simulations (DNS) which, in the context of the present study, is considered the exact…

Fluid Dynamics · Physics 2012-05-04 F. Bianco , S. Chibbaro , C. Marchioli , M. V. Salvetti , A. Soldati

Due to computational constraints, climate simulations cannot resolve a range of small-scale physical processes, which have a significant impact on the large-scale evolution of the climate system. Parameterization is an approach to capture…

Atmospheric and Oceanic Physics · Physics 2024-11-12 Cem Gultekin , Adam Subel , Cheng Zhang , Matan Leibovich , Pavel Perezhogin , Alistair Adcroft , Carlos Fernandez-Granda , Laure Zanna

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

Computational Physics · Physics 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw

Ocean eddies are swirling mesoscale features that play a fundamental role in oceanic transport and mixing. Eddy identification relies on diagnostic criteria that are inherently nonlinear functions of the flow variables. However, estimating…

Geophysics · Physics 2025-10-06 Charlotte Moser , Nan Chen , Stephen Wiggins

Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian nature of turbulence. That suggests that…

Computational Engineering, Finance, and Science · Computer Science 2019-09-24 Mehdi Samiee , Ali Akhavan-Safaei , Mohsen Zayernouri

A simple variant of recycling and rescaling method to generate inflow turbulence using unstructured grid CFD codes is presented. The method has been validated on large eddy simulation of spatially developing flat plate turbulent boundary…

Fluid Dynamics · Physics 2014-08-22 Sunil K. Arolla

Direct numerical simulation (DNS), mostly used in fundamental turbulence research, is limited to low turbulent intensities due the current and future computer resources. Standard turbulence models, like RaNS (Reynolds averaged…

Fluid Dynamics · Physics 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

We present a variant of the immersed boundary method integrated with octree meshes for highly efficient and accurate Large-Eddy Simulations (LES) of flows around complex geometries. We demonstrate the scalability of the proposed method up…

One issue associated with the use of Large-Eddy Simulation (LES) to investigate the dispersion of small inertial particles in turbulent flows is the accuracy with which particle statistics and concentration can be reproduced. The motion of…

Super-resolution techniques overcome the diffraction-limit and get very high resolutions. A category of these techniques, e.g., STED achieves this by creating an illumination spot smaller than the Airy Disk. As a result, points are…

Image and Video Processing · Electrical Eng. & Systems 2019-11-20 Yaohua Xie

Hybrid Reynolds-averaged Navier Stokes large eddy simulation (RANS LES) methods have become popular for simulation of massively separated flows at high Reynolds numbers due to their reduced computational cost and good accuracy. The current…

Fluid Dynamics · Physics 2021-02-19 Gaurav Kumar , Ashoke De , Harish Gopalan

A high-order flux reconstruction solver has been developed and validated to perform implicit large-eddy simulations of industrially representative turbomachinery flows. The T106c low-pressure turbine and VKI LS89 high-pressure turbine cases…

Fluid Dynamics · Physics 2024-07-26 Feng Wang

Grid adaptation for implicit Large Eddy Simulation (LES) is a non-trivial challenge due to the inherent coupling of the modeling and numerical errors. An attempt to address the challenge first requires a comprehensive assessment and then…

Numerical Analysis · Mathematics 2020-11-09 Yao Jiang , Siva Nadarajah

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

Fluid Dynamics · Physics 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia

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

We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large…

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