scholarly journals Publisher’s Note: “Effect of grid resolution on large eddy simulation of wall-bounded turbulence” [Phys. Fluids 30, 055106 (2018)]

2018 ◽  
Vol 30 (7) ◽  
pp. 079901
Author(s):  
S. Rezaeiravesh ◽  
M. Liefvendahl
Keyword(s):  
Large Eddy Simulation ◽  
Grid Resolution ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Wall Bounded Turbulence

Kinetic-energy-flux-constrained model using an artificial neural network for large-eddy simulation of compressible wall-bounded turbulence

2021 ◽  
Vol 932 ◽  
Author(s):  
Changping Yu ◽  
Zelong Yuan ◽  
Han Qi ◽  
Jianchun Wang ◽  
Xinliang Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Energy Flux ◽  
Mean Velocity ◽  
New Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Wall Bounded Turbulence

Kinetic energy flux (KEF) is an important physical quantity that characterizes cascades of kinetic energy in turbulent flows. In large-eddy simulation (LES), it is crucial for the subgrid-scale (SGS) model to accurately predict the KEF in turbulence. In this paper, we propose a new eddy-viscosity SGS model constrained by the properly modelled KEF for LES of compressible wall-bounded turbulence. The new methodology has the advantages of both accurate prediction of the KEF and strong numerical stability in LES. We can obtain an approximate KEF by the tensor-diffusivity model, which has a high correlation with the real value. Then, using the artificial neural network method, the local ratios between the real KEF and the approximate KEF are accurately modelled. Consequently, the SGS model can be improved by the product of that ratio and the approximate KEF. In LES of compressible turbulent channel flow, the new model can accurately predict mean velocity profile, turbulence intensities, Reynolds stress, temperature–velocity correlation, etc. Additionally, for the case of a compressible flat-plate boundary layer, the new model can accurately predict some key quantities, including the onset of transitions and transition peaks, the skin-friction coefficient, the mean velocity in the turbulence region, etc., and it can also predict the energy backscatters in turbulence. Furthermore, the proposed model also shows more advantages for coarser grids.

scholarly journals Vertically nested LES for high-resolution simulation of the surface layer in PALM (version 5.0)

2019 ◽  
Vol 12 (6) ◽  
pp. 2523-2538 ◽  
Author(s):  
Sadiq Huq ◽  
Frederik De Roo ◽  
Siegfried Raasch ◽  
Matthias Mauder
Keyword(s):  
Boundary Layer ◽  
Surface Layer ◽  
High Resolution ◽  
Large Eddy Simulation ◽  
Grid Resolution ◽  
Computational Power ◽  
Fine Grid ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Nesting Algorithm

Abstract. Large-eddy simulation (LES) has become a well-established tool in the atmospheric boundary layer research community to study turbulence. It allows three-dimensional realizations of the turbulent fields, which large-scale models and most experimental studies cannot yield. To resolve the largest eddies in the mixed layer, a moderate grid resolution in the range of 10 to 100 m is often sufficient, and these simulations can be run on a computing cluster with a few hundred processors or even on a workstation for simple configurations. The desired resolution is usually limited by the computational resources. However, to compare with tower measurements of turbulence and exchange fluxes in the surface layer, a much higher resolution is required. In spite of the growth in computational power, a high-resolution LES of the surface layer is often not feasible: to fully resolve the energy-containing eddies near the surface, a grid spacing of O(1 m) is required. One way to tackle this problem is to employ a vertical grid nesting technique, in which the surface is simulated at the necessary fine grid resolution, and it is coupled with a standard, coarse, LES that resolves the turbulence in the whole boundary layer. We modified the LES model PALM (Parallelized Large-eddy simulation Model) and implemented a two-way nesting technique, with coupling in both directions between the coarse and the fine grid. The coupling algorithm has to ensure correct boundary conditions for the fine grid. Our nesting algorithm is realized by modifying the standard third-order Runge–Kutta time stepping to allow communication of data between the two grids. The two grids are concurrently advanced in time while ensuring that the sum of resolved and sub-grid-scale kinetic energy is conserved. We design a validation test and show that the temporally averaged profiles from the fine grid agree well compared to the reference simulation with high resolution in the entire domain. The overall performance and scalability of the nesting algorithm is found to be satisfactory. Our nesting results in more than 80 % savings in computational power for 5 times higher resolution in each direction in the surface layer.

scholarly journals The Effect of Mesh Resolution on Convective Boundary Layer Statistics and Structures Generated by Large-Eddy Simulation

2011 ◽  
Vol 68 (10) ◽  
pp. 2395-2415 ◽  
Author(s):  
Peter P. Sullivan ◽  
Edward G. Patton
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Grid Resolution ◽  
Inertial Subrange ◽  
Entrainment Rate ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Eddy Simulation ◽  
Solution Convergence ◽  
Large Eddy

Abstract A massively parallel large-eddy simulation (LES) code for planetary boundary layers (PBLs) that utilizes pseudospectral differencing in horizontal planes and solves an elliptic pressure equation is described. As an application, this code is used to examine the numerical convergence of the three-dimensional time-dependent simulations of a weakly sheared daytime convective PBL on meshes varying from 323 to 10243 grid points. Based on the variation of the second-order statistics, energy spectra, and entrainment statistics, LES solutions converge provided there is adequate separation between the energy-containing eddies and those near the filter cutoff scale. For the convective PBL studied, the majority of the low-order moment statistics (means, variances, and fluxes) become grid independent when the ratio zi/(CsΔf) > 310, where zi is the boundary layer height, Δf is the filter cutoff scale, and Cs is the Smagorinsky constant. In this regime, the spectra show clear Kolmogorov inertial subrange scaling. The bulk entrainment rate determined from the time variation of the boundary layer height we = dzi/dt is a sensitive measure of the LES solution convergence; we becomes grid independent when the vertical grid resolution is able to capture both the mean structure of the overlying inversion and the turbulence. For all mesh resolutions used, the vertical temperature flux profile varies linearly over the interior of the boundary layer and the minimum temperature flux is approximately −0.2 of the surface heat flux. Thus, these metrics are inadequate measures of solution convergence. The variation of the vertical velocity skewness and third-order moments expose the LES’s sensitivity to grid resolution.

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