Application of High-Resolution Large Eddy Simulation to Simplified Turbomachinery Flows

Author(s):  
Susumu Teramoto ◽  
Takuya Ouchi ◽  
Hiroki Sanada ◽  
Koji Okamoto

Fully resolved large eddy simulation (LES) is applied to two simple geometry flowfields with well-defined boundary conditions. The LES results are compared with simulations based on a Reynolds-averaged Navier-Stokes (RANS) model with turbulence, and pros and cons of using high-resolution LES for turbomachinery flows are discussed. One flow is a linear compressor cascade flow composed of the tip section of GE rotor B at Rec = 4 × 105 with a clearance, and the other is a Mach 1.76 supersonic turbulent boundary layer at Reδ = 5000 that laminerizes through a 12-degree expansion corner. The grids are prepared fine enough to resolve the turbulent boundary layer through a grid sensitivity study. The liner cascade result shows that all the turbulent shear layers and boundary layers including those in the small tip clearance are well resolved with 800 million grid points. The Reynolds stress derived from the LES results are compared directly with those predicted from the Spalart-Allmaras one-equation RANS turbulence model. The two results agreed qualitatively well except for the shear layer surrounding the tip leakage vortex, demonstrating that the RANS model performs well at least for flowfields near the design condition. From the simulation of the turbulent boundary layer experiencing sudden expansion, noticeable decreases of both Reynolds stress and local friction coefficient were observed, showing that the turbulent boundary layer has relaminarized through the sudden expansion. The boundary layer downstream of the expansion exhibits a nonequilibrium condition and was different from the laminar boundary layer.

PAMM ◽  
2008 ◽  
Vol 8 (1) ◽  
pp. 10099-10102
Author(s):  
Nikolaus Peller ◽  
Michael Manhart

2021 ◽  
Vol 33 (12) ◽  
pp. 125116
Author(s):  
Yongchao Ji ◽  
Zhou Jiang ◽  
Zhenhua Xia ◽  
Shiyi Chen

2019 ◽  
Vol 12 (6) ◽  
pp. 2523-2538 ◽  
Author(s):  
Sadiq Huq ◽  
Frederik De Roo ◽  
Siegfried Raasch ◽  
Matthias Mauder

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.


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