The Effects Of Blade Count On Boundary Layer Development In A Low Pressure Turbine PDF Download

Detailed experimental investigation has been conducted to provide a detailed insight into the heat transfer and aerodynamic behavior of a separation zone that is generated as a result of boundary layer development along the suction surface of a highly loaded low pressure turbine (LPT) blade. The research experimentally investigates the individual and combined effects of periodic unsteady wake flows and freestream turbulence intensity (Tu) on heat transfer and aerodynamic behavior of the separation zone. Heat transfer experiments were carried out at Reynolds number of 110,000, 150,000, and 250,00 based on the suction surface length and the cascade exit velocity. Aerodynamic experiments were performed at Re = 110,000 and 150,000. For the above Re-numbers, the experimental matrix includes Tus of 1.9%, 3.0%, 8.0%,13.0% and three different unsteady wake frequencies with the steady inlet flow as the reference configuration. Detailed heat transfer and boundary layer measurements are performed with particular attention paid to the heat transfer and aerodynamic behavior of the separation zone at different Tus at steady and periodic unsteady flow conditions. The objectives of the research are (a) to quantify the effect of Tu on the aero-thermal behavior of the separation bubble at steady inlet flow condition, (b) to investigate the combined effects of Tu and the unsteady wake flow on the aero-thermal behavior of the separation bubble, and (c) to provide a complete set of heat transfer and aerodynamic data for numerical simulation that incorporates Navier-Stokes and energy equations. The analysis of the experimental data reveals details of boundary layer separation dynamics which is essential for understanding the physics of the separation phenomenon under periodic unsteady wake flow and different Reynolds number and Tu. To provide a complete picture of the transition process and separation dynamics, extensive intermittency analysis was conducted. Ensemble averaged maximum and minimum intermittency functions were determined leading to the relative intermittency function. In addition, the detailed intermittency analysis reveals that the relative intermittency factor follows a Gaussian distribution confirming the universal character of the relative intermittency function.