Numerical investigations of separation-induced transition on high-lift low-pressure turbine using RANS and LES methods

J Marty - Proceedings of the Institution of Mechanical …, 2014 - journals.sagepub.com
Proceedings of the Institution of Mechanical Engineers, Part A …, 2014journals.sagepub.com
At low Reynolds numbers, laminar-turbulent transition occurs on the suction side of high-lift
low-pressure turbine blades. The prediction of this flow is an important step in low-pressure
turbine design. Thus, the laminar-turbulent transition must be modeled or resolved. The flow
around the high-lift low-pressure turbine blade T106C is predicted using Reynolds-
Averaged Navier-Stokes (RANS) simulations, without and with transition model, and large-
eddy simulations (LES). LES are performed in order to predict the laminar separation bubble …
At low Reynolds numbers, laminar-turbulent transition occurs on the suction side of high-lift low-pressure turbine blades. The prediction of this flow is an important step in low-pressure turbine design. Thus, the laminar-turbulent transition must be modeled or resolved. The flow around the high-lift low-pressure turbine blade T106C is predicted using Reynolds-Averaged Navier-Stokes (RANS) simulations, without and with transition model, and large-eddy simulations (LES). LES are performed in order to predict the laminar separation bubble (LSB) without any laminar-turbulent transition modeling. Only two Reynolds numbers are investigated with LES, and the current study concerns also the validation of the turbulent random flow generation technique of Smirnov et al. Reynolds number and freestream turbulence effects are studied using the analysis of the unsteady behavior of the separated shear layer and the bubble. The steady flow predicted by RANS simulation with transition model and by the time-averaged LES are in good agreement with isentropic Mach number distribution at mid-span, except for the lowest Reynolds number (Re2is = 80,000). For this last case, the separation and transition points are predicted downstream of the experimental points. The spectral analysis of LES results at different locations allows determining specific frequencies of physical mechanisms. LES are able to predict LSB over the high-lift low-pressure turbine blade T106C as RANS simulation with transition model and to capture the Kelvin–Helmholtz instability which is the cause of the transition mechanism.
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