Multi-resolution implicit large eddy simulations using a high-order overset-grid approach

2007 ◽  
Vol 55 (5) ◽  
pp. 455-482 ◽  
Author(s):  
S. E. Sherer ◽  
M. R. Visbal
Keyword(s):  
High Order ◽  
Large Eddy Simulations ◽  
Overset Grid ◽  
Grid Approach ◽  
Large Eddy

A High-Order Overset-Grid Approach for Large Eddy Simulations

2007 ◽  
Author(s):  
Scott E. Sherer ◽  
Miguel R. Visbal ◽  
Raymond E. Gordnier
Keyword(s):  
Delta Wing ◽  
Temporal Integration ◽  
Grid Method ◽  
Current Method ◽  
Turbulent Channel Flow ◽  
High Order ◽  
Overset Grid ◽  
Time Step ◽  
Grid Approach ◽  
Large Eddy

A parallel, high-order, overset-grid method is validated for use in large eddy simulation (LES) through its application to turbulent flow problems. The current method employs a high-order, compact finite-difference approach to evaluate spatial derivatives, with up-to-tenth-order low-pass filters used to remove high-frequency spurious wave content. These filters have also been found to be effective in modeling the dissipation that occurs at the unresolved scales in the flow for LES simulations. Temporal integration is based on an implicit, approximately-factored and diagonalized, second-order algorithm, which reduces the time-step constraints present in explicit time-marching methods for wall-bounded viscous flows. Parallelization, geometric complexity, and local grid refinement are all addressed through the use of an overset-grid approach, with grid communication provided by high-order Lagrangian interpolation. Problems demonstrating this approach include fully turbulent channel flow and flows over a single circular cylinder, a general delta-wing configuration, and a realistic UAV geometry.

scholarly journals Performance of high-order implicit large eddy simulations

2018 ◽  
Vol 173 ◽  
pp. 307-312 ◽  
Author(s):  
Konstantinos Ritos ◽  
Ioannis W. Kokkinakis ◽  
Dimitris Drikakis
Keyword(s):  
High Order ◽  
Large Eddy Simulations ◽  
Large Eddy

scholarly journals Impact of Number Representation for High-Order Implicit Large-Eddy Simulations

AIAA Journal ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 184-197
Author(s):  
F. D. Witherden ◽  
A. Jameson
Keyword(s):  
High Order ◽  
Large Eddy Simulations ◽  
Number Representation ◽  
Large Eddy

Large Eddy Simulations for 3D Turbine Blades Using a High Order Flux Reconstruction Method

2013 ◽  
Author(s):  
Yi Lu ◽  
Kai Liu ◽  
W. N. Dawes
Keyword(s):  
Turbine Blade ◽  
High Order ◽  
Large Eddy Simulations ◽  
Complex Geometries ◽  
Flux Reconstruction ◽  
Reconstruction Method ◽  
Order Accuracy ◽  
Local Reconstruction ◽  
Low Pressure Turbine ◽  
Large Eddy

During the last decades, the improvements of both computational ability and numerical schemes have stimulated increasing industrial interest in the use of Large Eddy Simulations (LES) for practical engineering flow problems. However, almost all current approches cannot treat complex geometries at affordable cost to enable LES of industrial problems. A robust, parallel and efficient solver using a general unstructured grid & based on high order flux reconstruction formulation, which uses local reconstruction, is compact and written in differential form without a mass matrix, was developed and has proved the ability to get accurate LES results but using RANS scale meshes. This work is aimed at using flux reconstruction method to perform Large Eddy Simulations for complex geometries in more robust and highly efficient way. Both explicit Runge-Kutta method and implicit LU-SGS method are implemented with improvements as solvers for better performance on boundary layer meshes including large aspect ratio cells. The current solver is ported to GPU architectures and speed up ratios of different order accuracy are presented in this work. A local reconstruction method is introduced to generate high order curved boundary from readily available first order meshes. The large eddy simulations for low pressure turbine blade and low pressure turbine blade with endwall are presented in this work, resolved with total number of degree of freedoms up to 34 million to chieve fourth order accuracy using limited computational resource. The results show that this approach has the potential to obtain LES results of real-geometry problems with affordable computational costs.

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