Differential filters for the large eddy numerical simulation of turbulent flows

1986 ◽  
Vol 29 (6) ◽  
pp. 1755 ◽  
Author(s):  
M. Germano
Keyword(s):  
Numerical Simulation ◽  
Turbulent Flows ◽  
Large Eddy

scholarly journals MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows

2017 ◽  
Vol 10 (8) ◽  
pp. 3145-3165 ◽  
Author(s):  
Chiel C. van Heerwaarden ◽  
Bart J. H. van Stratum ◽  
Thijs Heus ◽  
Jeremy A. Gibbs ◽  
Evgeni Fedorovich ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Numerical Simulation ◽  
Computational Fluid Dynamics ◽  
Large Eddy Simulation ◽  
Direct Numerical Simulation ◽  
Turbulent Flows ◽  
Processing Unit ◽  
Moist Convection ◽  
Eddy Simulation ◽  
Large Eddy

Abstract. This paper describes MicroHH 1.0, a new and open-source (www.microhh.org) computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is primarily made for direct numerical simulation but also supports large-eddy simulation (LES). The paper covers the description of the governing equations, their numerical implementation, and the parameterizations included in the code. Furthermore, the paper presents the validation of the dynamical core in the form of convergence and conservation tests, and comparison of simulations of channel flows and slope flows against well-established test cases. The full numerical model, including the associated parameterizations for LES, has been tested for a set of cases under stable and unstable conditions, under the Boussinesq and anelastic approximations, and with dry and moist convection under stationary and time-varying boundary conditions. The paper presents performance tests showing good scaling from 256 to 32 768 processes. The graphical processing unit (GPU)-enabled version of the code can reach a speedup of more than an order of magnitude for simulations that fit in the memory of a single GPU.

Large Eddy Simulation

1996 ◽  
Author(s):  
Joel H. Ferziger
Keyword(s):  
Numerical Simulation ◽  
Large Eddy Simulation ◽  
Direct Numerical Simulation ◽  
Turbulent Flow ◽  
Turbulent Flows ◽  
Flow Simulation ◽  
Simulation Methods ◽  
Eddy Simulation ◽  
Simulation Techniques ◽  
Large Eddy

Over a decade ago, the author (Ferziger, 1983) wrote a review of the then state-of-the-art in direct numerical simulation (DNS) and large eddy simulation (LES). Shortly thereafter, a second review was written by Rogallo and Moin (1984). In those relatively early days of turbulent flow simulation, it was possible to write comprehensive reviews of what had been accomplished. Since then, the widespread availability of supercomputers has led to an explosion in this field so, although the subject is undoubtedly overdue for another review, it is not clear that the task can be accomplished in anything less than a monograph. The author therefore apologizes in advance for omissions (there must be many) and for any bias toward the accomplishments of people on the west coast of North America. In the earlier review, the author listed six approaches to the prediction of turbulent flow behavior. The list included: correlations, integral methods, single-point Reynolds-averaged closures, two-point closures, large eddy simulation and direct numerical simulation. Even then the distinction between these methods was not always clear; if anything, it is less clear today. It was possible in the earlier review to give a relatively complete overview of what had been accomplished with simulation methods. Since then, simulation techniques have been applied to an ever expanding range of flows so a thorough review of simulation results is no longer possible in the space available here. Simulation techniques have become well established as a means of studying turbulent flows and the results of simulations are best presented in combination with experimental data for the same flow. There is also a danger that the success of simulation methods will lead to attempts to apply them too soon to flows which the models and techniques are not ready to handle. To some extent, this is already happening. Direct numerical simulation (DNS) is a method in which all of the scales of motion of a turbulent flow are computed. A DNS must include everything from the large energy-containing or integral scales to the dissipative scales; the latter is usually taken to be the viscous or Kolmogoroff scales.

scholarly journals MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows

2017 ◽  
Author(s):  
Chiel C. van Heerwaarden ◽  
Bart J. H. van Stratum ◽  
Thijs Heus ◽  
Jeremy A. Gibbs ◽  
Evgeni Fedorovich ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Numerical Simulation ◽  
Computational Fluid Dynamics ◽  
Large Eddy Simulation ◽  
Direct Numerical Simulation ◽  
Turbulent Flows ◽  
Processing Unit ◽  
Moist Convection ◽  
Eddy Simulation ◽  
Large Eddy

Abstract. This paper describes MicroHH 1.0, a new and open source (www.microhh.org) computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is primarily made for direct numerical simulation, but also supports large-eddy simulation (LES). The paper covers the description of the governing equations, their numerical implementation, and the parametrizations included in the code. Furthermore, the paper presents the validation of the dynamical core in the form of convergence and conservation tests, and comparison of simulations of channel flows and slope flows against well-established test cases. The full numerical model, including the associated parametrizations for LES, has been tested for a set of cases under stable and unstable conditions, under the Boussinesq and anelastic approximation, and with dry and moist convection under stationary and time-varying boundary conditions. The paper presents performance tests showing good scaling from 256 to 32,768 processes. The Graphical Processing Unit-enabled version of the code reaches speedups of more than an order of magnitude with respect to the conventional code for a variety of cases.

Simulation and Modeling of Turbulent Flows

1996 ◽  
Keyword(s):  
Numerical Simulation ◽  
Turbulent Flow ◽  
Turbulent Flows ◽  
Simulation And Modeling ◽  
Simulation Techniques ◽  
Rational Development ◽  
Group Methods ◽  
Turbulent Closure ◽  
The Subject ◽  
Renormalization Group Methods

This book provides students and researchers in fluid engineering with an up-to-date overview of turbulent flow research in the areas of simulation and modeling. A key element of the book is the systematic, rational development of turbulence closure models and related aspects of modern turbulent flow theory and prediction. Starting with a review of the spectral dynamics of homogenous and inhomogeneous turbulent flows, succeeding chapters deal with numerical simulation techniques, renormalization group methods and turbulent closure modeling. Each chapter is authored by recognized leaders in their respective fields, and each provides a thorough and cohesive treatment of the subject.

scholarly journals Large-eddy simulation of wall-bounded turbulent flow with high-order discrete unified gas-kinetic scheme

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Rui Zhang ◽  
Chengwen Zhong ◽  
Sha Liu ◽  
Congshan Zhuo
Keyword(s):  
Turbulent Flow ◽  
Turbulent Flows ◽  
Parallel Implementation ◽  
Kinetic Scheme ◽  
Cavity Flow ◽  
Equilibrium Distribution Function ◽  
Third Order ◽  
Two Stage ◽  
Large Eddy ◽  
Unified Gas Kinetic Scheme

AbstractIn this paper, we introduce the discrete Maxwellian equilibrium distribution function for incompressible flow and force term into the two-stage third-order Discrete Unified Gas-Kinetic Scheme (DUGKS) for simulating low-speed turbulent flows. The Wall-Adapting Local Eddy-viscosity (WALE) and Vreman sub-grid models for Large-Eddy Simulations (LES) of turbulent flows are coupled within the present framework. Meanwhile, the implicit LES are also presented to verify the effect of LES models. A parallel implementation strategy for the present framework is developed, and three canonical wall-bounded turbulent flow cases are investigated, including the fully developed turbulent channel flow at a friction Reynolds number (Re) about 180, the turbulent plane Couette flow at a friction Re number about 93 and lid-driven cubical cavity flow at a Re number of 12000. The turbulence statistics, including mean velocity, the r.m.s. fluctuations velocity, Reynolds stress, etc. are computed by the present approach. Their predictions match precisely with each other, and they are both in reasonable agreement with the benchmark data of DNS. Especially, the predicted flow physics of three-dimensional lid-driven cavity flow are consistent with the description from abundant literature. The present numerical results verify that the present two-stage third-order DUGKS-based LES method is capable for simulating inhomogeneous wall-bounded turbulent flows and getting reliable results with relatively coarse grids.

Simulating flow separation from continuous surfaces: routes to overcoming the Reynolds number barrier

2009 ◽  
Vol 367 (1899) ◽  
pp. 2885-2903 ◽  
Author(s):  
Michael Leschziner ◽  
Ning Li ◽  
Fabrizio Tessicini
Keyword(s):  
Reynolds Number ◽  
Turbulent Flows ◽  
Major Elements ◽  
Wall Layer ◽  
Navier Stokes ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Rans Models ◽  
High Reynolds ◽  
Near Wall

This paper provides a discussion of several aspects of the construction of approaches that combine statistical (Reynolds-averaged Navier–Stokes, RANS) models with large eddy simulation (LES), with the objective of making LES an economically viable method for predicting complex, high Reynolds number turbulent flows. The first part provides a review of alternative approaches, highlighting their rationale and major elements. Next, two particular methods are introduced in greater detail: one based on coupling near-wall RANS models to the outer LES domain on a single contiguous mesh, and the other involving the application of the RANS and LES procedures on separate zones, the former confined to a thin near-wall layer. Examples for their performance are included for channel flow and, in the case of the zonal strategy, for three separated flows. Finally, a discussion of prospects is given, as viewed from the writer's perspective.

On Direct Numerical Simulation of Turbulent Flows

2011 ◽  
Vol 64 (2) ◽  
Author(s):  
Giancarlo Alfonsi
Keyword(s):  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
High Performance Computing ◽  
Turbulent Flows ◽  
High Performance ◽  
Stokes Equations ◽  
Navier Stokes ◽  
Turbulent Shear ◽  
Navier Stokes Equations ◽  
Performance Computing

The direct numerical simulation of turbulence (DNS) has become a method of outmost importance for the investigation of turbulence physics, and its relevance is constantly growing due to the increasing popularity of high-performance-computing techniques. In the present work, the DNS approach is discussed mainly with regard to turbulent shear flows of incompressible fluids with constant properties. A body of literature is reviewed, dealing with the numerical integration of the Navier-Stokes equations, results obtained from the simulations, and appropriate use of the numerical databases for a better understanding of turbulence physics. Overall, it appears that high-performance computing is the only way to advance in turbulence research through the front of the direct numerical simulation.

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