Numerical Investigation of Loss Development in a Low-Pressure Turbine Cascade With Unsteady Inflow and Varying Inlet Endwall Boundary Layer

An investigation of endwall loss development is conducted using the T106A low-pressure turbine cascade. (U)RANS simulations are complemented by measurements under engine relevant flow conditions (M2th = 0.59, Re2th = 2·105). The effects of unsteady inflow conditions and varying inlet endwall boundary layer are compared in terms of secondary flow attenuation downstream of the blade passage, analyzing steady, time-averaged, and time-resolved flow fields. While both measures show similar effects in the turbine exit plane, the upstream loss development throughout the blade passage is quite different. A variation of the endwall boundary layer alters the slope of the axial loss generation beginning around the midpoint of the blade passage. Periodically incoming wakes, however, cause a spatial redistribution of the loss generation with a premature loss increase due to wake interaction in the front part of the passage followed by an attenuation of the profile- and secondary loss generation in the aft section of the blade passage. Ultimately, this leads to a convergence of the downstream loss values in the steady and unsteady inflow cases.

The Effects of Inlet Boundary Layer Condition and Periodically Incoming Wakes on Secondary Flow in a Low Pressure Turbine Cascade

A particular turbine cascade design is presented with the goal of providing a basis for high quality investigations of endwall flow at high-speed flow conditions and unsteady inflow. The key feature of the design is an integrated two-part flat plate serving as a cascade endwall at part-span, which enables a variation of the inlet endwall boundary layer conditions. The new design is applied to the T106A low pressure turbine cascade for endwall flow investigations in the High-Speed Cascade Wind Tunnel of the Institute of Jet Propulsion at the Bundeswehr University Munich. Measurements are conducted at realistic flow conditions (M2th = 0.59, Re2th = 200 000) in three cases of different endwall boundary layer conditions with and without periodically incoming wakes. The endwall boundary layer is characterized by 1DCTA measurements upstream of the blade passage. Secondary flow is evaluated by Five-hole-probemeasurements in the turbine exit flow. A strong similarity is found between the time-averaged effects of unsteady inflow conditions and the effects of changing inlet endwall boundary layer conditions regarding the attenuation of secondary flow. Furthermore, the experimental investigations show, that all design goals for the improved T106A cascade are met.

The Effects of Inlet Boundary Layer Condition and Periodically Incoming Wakes on Secondary Flow in a Low Pressure Turbine Cascade

A particular turbine cascade design is presented with the goal of providing a basis for high quality investigations of endwall flow at high-speed flow conditions and unsteady inflow. The key feature of the design is an integrated two-part flat plate serving as a cascade endwall at part-span, which enables a variation of the inlet endwall boundary layer conditions. The new design is applied to the T106A low pressure turbine cascade for endwall flow investigations in the High-Speed Cascade Wind Tunnel of the Institute of Jet Propulsion at the Bundeswehr University Munich. Measurements are conducted at realistic flow conditions (M2th = 0.59, Re2th = 2·105) in three cases of different endwall boundary layer conditions with and without periodically incoming wakes. The endwall boundary layer is characterized by 1D-CTA measurements upstream of the blade passage. Secondary flow is evaluated by Five-hole-probe measurements in the turbine exit flow. A strong similarity is found between the time-averaged effects of unsteady inflow conditions and the effects of changing inlet endwall boundary layer conditions regarding the attenuation of secondary flow. Furthermore, the experimental investigations show, that all design goals for the improved T106A cascade are met.

Machine-Learnt Turbulence Closures for Low-Pressure Turbines With Unsteady Inflow Conditions

The design of low-pressure turbines (LPTs) must account for the losses generated by the unsteady interaction with the upstream blade row. The estimation of such unsteady wake-induced losses requires the accurate prediction of the incoming wake dynamics and decay. Existing linear turbulence closures (stress–strain relationships), however, do not offer an accurate prediction of the wake mixing. Therefore, machine-learnt, nonlinear turbulence closures (models) have been developed for LPT flows with unsteady inflow conditions using a zonal-based model development approach, with an aim to enhance the wake mixing prediction for unsteady Reynolds-averaged Navier–Stokes calculations. High-fidelity time-averaged and phase-lock averaged data at a realistic isentropic Reynolds number and two reduced frequencies, i.e., with discrete incoming wakes and with wake “fogging,” have been used as reference data for a machine learning algorithm based on gene expression programing to develop models. Models developed via phase-lock averaged data were able to capture the effect of certain prominent physical phenomena in LPTs such as wake–wake interactions, whereas models based on the time-averaged data could not. Correlations with the flow physics lead to a set of models that can effectively enhance the wake mixing prediction across the entire LPT domain for both cases. Based on a newly developed error metric, the developed models have reduced the a priori error over the Boussinesq approximation on average by 45%. This study thus aids blade designers in selecting the appropriate nonlinear closures capable of mimicking the physical mechanisms responsible for loss generation.