PhD, University of Cincinnati, 2008, Engineering : Mechanical Engineering
The operating Reynolds numbers (Re) for a low-pressure turbine (LPT) in an aircraft engine can drop below 25,000 during high-altitude cruise conditions, resulting in massive separation and subsequent transition on the blade suction surface. This separation causes a significant loss in the engine efficiency. Hence, accurate prediction of the flow physics at these low-Re conditions is required to effectively implement flow control techniques which can help mitigate separation-induced losses. The present work investigated this low-Re transitional flow through a LPT cascade comprised of the generic Pratt & Whitney “PAKB” blades, using high-order accurate compact numerical schemes in conjunction with large-eddy simulation (LES), with and without subgrid-scale (SGS) models. The study examined the predictive capability of the explicit Smagorinsky and dynamic Smagorinsky SGS models, as compared to the Implicit LES (ILES) technique (LES without an explicit SGS model). The research also implemented active flow control on the LPT blades using momentum injection via surface blowing. All simulations utilized a dual-topology, multi-block, structured grid, and computations were performed on a massively parallel computing platform using MPI-based communications. The baseline cases (without control) were simulated at Re ~ 10,000, 25,000 and 50,000. The computed numerical results for all three cases showed good agreement with available experimental data. The Smagorinsky and dynamic Smagorinsky SGS model results provided no significant improvement over the ILES results because of the low level of energy in the subgrid-scales for the present low-Re flow conditions investigated, and hence, the ILES technique was used for all subsequent flow-control simulations. Separation control of the LPT flow was implemented using synthetic normal jets, synthetic vortex-generator jets, and pulsed vortex-generator jets (VGJs) at Re ~ 10,000, for four blowing ratios ranging from 0.5 to 4.7, where the b (open full item for complete abstract)
Committee: Urmila Ghia (Advisor)
Subjects: Engineering, Mechanical