Large Eddy Simulation of a High Pressure Turbine Stage: Effects of Sub-Grid Scale Modeling and Mesh Resolution

Abstract

The use of Computational Fluid Dynamics (CFD) tools for integrated simulations of gas turbine components has emerged as a promising way to predict undesired component interactions thereby giving access to potentially better engine designs and higher efficiency. In this context, the ever-increasing computational power available worldwide makes it possible to envision integrated massively parallel combustion chamber-turbomachinery simulations based on Large-Eddy Simulations (LES). While LES have proven their superiority for combustor simulations, few studies have employed this approach in complete turbomachinery stages. The main reason for this is the known weaknesses of near wall flow modeling in CFD. Two approaches exist: the wall-modeled LES, where wall flow physics is modeled by a law-of-the-wall, and the wall-resolved LES where all the relevant near wall physics is to be captured by the grid leading to massive computational cost increases. This work investigates the sensitivity of wall-modeled LES of a high-pressure turbine stage. The code employed, called TurboAVBP, is an in-house LES code capable of handling turbomachinery configurations. This is possible through an LES-compatible approach with the rotor/stator interface treated based on an overset moving grids method. It is designed to avoid any interference with the numerical scheme, allow the proper representation of turbulent structures crossing it and run on massively parallel platforms. The simulations focus on the engine-representative MT1 transonic high-pressure turbine, tested by QinetiQ. To control the computational cost, the configuration employed is composed of 1 scaled stator section and 2 rotors. The main issues investigated are the effect of mesh resolution and the effect of sub-grid scale models in conjunction with wall modeling. The pressure profiles across the stator and rotor blades are in good agreement with the experimental data for all cases. Radial profiles at the rotor exit (in the near and far field) show improvement over RANS predictions. Unsteady flow features, inherently present in LES, are, however, found to be affected by the modeling parameters as evidenced by the obtained shock strengths and structures or turbulence content of the different simulations.

Prediction of the unsteady turbine trailing edge wake flow characteristics and comparison with experimental data

“…A classical problem of LES applied to high Reynolds flows is in fact the direct resolution of the small turbulent structures, generated very close to the wall and during the laminar to turbulent transition. 11 Despite this, because of the high turbulent energy content locally represented by the viscous turbulence and the limited difference in thickness with respect to the experimental profile, a satisfactory reproduction of the vortex shedding behavior is expected. Figure 7 represents the time-averaged static pressure distribution at the trailing edge.…”

“…To this end, Leonard studied also the possibility of performing LES on the same profile, obtaining encouraging results. The feasibility of LES on turbines is also discussed in detail by several authors such as Papadogiannis et al 11 and Tyacke et al, 12 who present interesting results on the flow structures that can be reproduced.…”

Impact of Wake Dispersion on Axial Compressor Performance

“…This negative generation process of the turbulent kinetic energy is not modeled in the frame of conventional RANS and URANS approaches. To obtain more and LES are being applied for turbomachinery flow analysis (Zaki et al [2010], Hah and Shin [2012], Gourdain [2013], Hah and Katz [2014], and Papadogiannis et al [2014]). The current paper is aimed to investigate rotor wake dispersion in the stator passage in detail.…”

Noise mechanisms in a transonic high-pressure turbine stage

“…19 It results in a domain with one stator blade and two rotors (12 degree periodicity) shown in Figure 1(b), for which the mean predicted aerodynamic flow field has already been extensively validated against experimental data. 20,21 The computational domain consists of two overlapping meshes covering the stator and the rotor, respectively. The unstructured hybrid meshes are generated using CENTAUR and include a prismatic boundary layer mesh 22,23 around the vane and blade surfaces while using tetrahedral cells away from these walls.…”