Low-pressure Turbine Cascade Research Articles

Optimization of Low-Pressure Turbine Blade by Means of Fine Inspection of Loss Production Mechanisms

Abstract In this study, Proper Orthogonal Decomposition (POD) was applied to Large Eddy Simulations (LES) of two high-loaded low-pressure turbine cascades under unsteady inflow conditions to investigate entropy production within different parts of the blade passage. The terms for Turbulent Kinetic Energy (TKE) production, diffusion, and dissipation from the stagnation pressure transport equation were integrated across the computational domain. The POD-based method enables the decomposition of contributions from various coherent flow dynamics to TKE production and dissipation, such as the migration, bowing, tilting, and reorientation of incoming wake filaments, as well as the breakdown of streaky structures in the blade boundary layer and the formation of Von Karman vortices in the blade wake. This approach helps designers identify the dominant POD modes (i.e., turbulent flow structures) responsible for loss generation, understand their dynamics and locate where they primarily act. Using this optimization strategy, a new low-pressure turbine profile was designed. LES calculations on the optimized geometry showed that it is possible to design a higher-loaded profile with a lower global loss coefficient. The new loading distribution, characterized by stronger acceleration in the early part of the blade passage, results in reduced upstream wake migration losses and lower TKE production in the trailing edge wake zone due to early suction side boundary layer transition.

Implementation of a high-order spatial discretization into a finite volume solver: Applications to turbomachinery test cases using an eddy-viscosity turbulence closure

In this study, the implementation of a high-order spatial discretization method into a Finite Volume solver is presented. Specific emphasis is put on the analysis of the performance over selected turbomachinery test cases. High-order numerical discretization is achieved by adopting the cell-centered Least-Square reconstruction, which is implemented in the in-house solver HybFlow. The validation of the adopted methodology is performed by assessing the solution of a turbulent flat plate with zero pressure gradient, using a eddy-viscosity transitional model. The test case also evidences the effect of the discretization of gradient-based source terms when a high-order reconstruction methodology is used. In the second part of the paper, the solver is used for the solution of relevant two-dimensional turbomachinery test cases, assessing the impact of 2nd and 3rd order reconstruction on the prediction of the aerodynamics and the heat transfer for respectively a low-pressure blade and a high-pressure turbine vane. It is shown how a high-order reconstruction allows for obtaining a better prediction of turbomachinery aerodynamics, with lower number of elements. The benefits over heat transfer predictions in high Reynolds number conditions are instead limited to the reduction of heat transfer coefficient spikes in under-resolved regions of the blade. Eventually, the methodology is validated for a three-dimensional low-pressure turbine cascade with realistic boundary layer inflow conditions.

Incidence Adaptation to the Influence of Wake Sweeps on the Aerodynamic Performance of a Low-Pressure Turbine Cascade

Incidence Adaptation to the Influence of Wake Sweeps on the Aerodynamic Performance of a Low-Pressure Turbine Cascade

Characterization of the Endwall Flow in a Low-Pressure Turbine Cascade Perturbed by Periodically Incoming Wakes, Part 1: Flow Field Investigations with Phase-Locked Particle Image Velocimetry

Particle image velocimetry (PIV) measurements were performed inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions to investigate the near-endwall flow. Of particular research interest was the dominant periodic disturbance of the flow field by incoming wakes, which were generated by moving cylindrical bars at a frequency of 500 Hz. Two PIV setups were utilized to resolve both (1) a large blade-to-blade plane close to the endwall as well as midspan and (2) the wake effects in an axial flow field downstream of the blade passage. The measurements were performed using a phase-locked approach in order to align and compare the results with comprehensive CFD data that are also available for this test case. The experimental results not only support a better understanding and even a quantification of the wake-induced over/under-turning inside and downstream of the passage, they also enable the tracing of the ‘negative-jet-effect’, which is widely known in the CFD branch of the turbomachinery community but is seldom visualized in experiments. The results also reveal that the bar wake periodically widens the blade wake by up to 165%, while the secondary flow is less affected and exhibits a phase lag with respect to the 2D-flow effects. The results presented here are an essential basis for the subsequent investigation of the near-endwall blade suction surface effects using unsteady pressure-sensitive paint in the second part of this two-part publication.

Characterization of the Endwall Flow in a Low-Pressure Turbine Cascade Perturbed by Periodically Incoming Wakes, Part 2: Unsteady Blade Surface Measurements Using Pressure-Sensitive Paint

Unsteady pressure-sensitive paint (i-PSP) measurements were performed at a sampling rate of 30 kHz to investigate the near-endwall blade suction surface flow inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions. The investigation focuses on the interaction of periodically incoming bar wakes at 500 Hz with the secondary flow and the blade suction surface. The results build on extensive PIV measurements presented in the first part of this two-part publication, which captured the ’negative-jet-effect’ of the wakes throughout the blade passage. The surface pressure distributions are combined with CFD to analyze the flow topology, such as the passage vortex separation line. By analyzing data from phase-locked PIV and PSP measurements, a wake-induced moving pressure gradient negative in space and positive in time is found, which is intensified in the secondary flow region by 33% with respect to midspan. Furthermore, two methods of frequency-filtering based on FFT and SPOD are compared and utilized to associate a pressure fluctuation peak around 678 Hz with separation bubble oscillation.

Local correlations for predicting the transition process in separated flows tuned with a large experimental database

This work provides new correlations based on local variables for characterizing the transition process developing in the case of separated flows. The goal is to improve the capability of correlation-based transition models through the use of local variables. This may indeed simplify the implementation of the correlations into modern numerical codes, especially dealing with parallel computation and unstructured meshes. A large experimental database considering about 90 different flow conditions has been used to tune the present correlations. The database accounts for the variation of the flow Reynolds number, the free-stream turbulence intensity and the adverse pressure gradient affecting the boundary layer developing over a flat plate. The parameter variation induces the formation of both short and long laminar separation bubbles. The vorticity Reynolds number, based on the second invariant of the vorticity tensor, has been used as the main local variable for the activation of the transition process. Since it is proportional to the momentum thickness Reynolds number at the separation position, the vorticity Reynolds number (local) can be used in place of its counterpart based on the momentum thickness (integral), which is the variable usually adopted for activation of transition. Then, correlations providing a critical threshold for the vorticity Reynolds number promoting transition are tuned, for both short and long bubbles. These may be used into transition models to directly provide the location where the turbulence production needs to be activated. The proposed correlations have been validated using a second database not adopted for tuning and finally tested with data concerning a separated flow case in a low-pressure turbine cascade.

Research on the Flow Mechanism of a High-Loading Biomimetic Low-Pressure Turbine Cascade

The biomimetic turbine has an excellent flow drag reduction ability and wide incidence adaptability, so it has the potential to achieve high efficiency within a wide working range of high-performance variable cycle engines. A biomimetic cascade that can broaden the effective working incidence angles was designed based on a high-loading low-pressure turbine cascade, and its flow mechanism and aerodynamic performance were studied using experimental and numerical methods under the incidences angle (i) of 0° to 15° and Reynolds number of 1.0 × 105. A series of counter rotating vortex pairs induced by the biomimetic cascade bring additional dissipation losses, but it accelerates the energy exchange between the boundary layer and mainstream, enhancing the dissipation of the pressure side leg of horseshoe vortex, and thus suppressing the flow separation and passage vortices. The undulating surface of biomimetic cascades can suppress the expansion of secondary flow in a spanwise direction in the end region, especially for large-scale separation under high incidence conditions. When i < 5°, the loss of biomimetic cascades is slightly higher than that of the original cascades, but the increase is only 0.5%; when i > 5°, the losses of biomimetic cascades are significantly reduced, with a maximum reduction of 70% at i = 15°.

Measurements of Turbulence in Compressible Low-Density Flows at the Inlet of a Transonic Linear Cascade With and Without Unsteady Wakes

Abstract In the present work, hot-wire anemometry was employed for the characterization of the turbulent field at the inlet of a high-speed low-pressure turbine cascade, in terms of turbulence intensity and integral length scales. This work addresses two major topics relevant to the turbomachinery field: the application of hot-wire anemometry in transonic and rarefied flow regimes and the decoupling of the deterministic and the stochastic fluctuations when measuring unsteady phenomena. In compressible and rarefied flows, a hot-wire is strongly sensitive to both density and velocity fluctuations, and the commonly used Nusselt–Reynolds correlations are not valid. In this article, a nondimensional calibration methodology, based on Nusselt, Reynolds, and Knudsen numbers, was coupled with a sensitivity analysis and employed to postprocess the experimental dataset, allowing to decouple the fluctuations of density and velocity and to compute the turbulence parameters. In the presence of unsteady wakes generated upstream of the cascade, two different phase-locked averaging techniques were employed to distinguish the wake deterministic fluctuations from the background turbulence intensity.

Experimental Investigation of Additional Loss Associated With Incoming Wakes in Low-Pressure Turbine Cascades

Abstract The present paper aims to experimentally investigate the influence of wake-passing frequency, Reynolds number, and suction surface diffusion rate on the additional loss due to incoming wakes to the profile loss in the low-pressure turbine (LPT) cascades and discuss a design guide for reducing the additional loss. Using a moving-bar mechanism, the unsteady effects of incoming wakes were measured in a low-speed linear turbine cascade facility. The wake-passing frequency was varied by adjusting the moving-bar speed. The different airfoils with different surface velocity distributions were tested to examine the effect of suction surface diffusion rate. For each test case in an unsteady flow condition, the additional loss due to incoming wakes was derived by subtracting the profile loss from the measured total pressure loss across the cascade. Here, the profile loss was estimated by using the friction drag force, which was calculated by the measured surface velocity distribution, and the pressure drag force, which was calculated by the measured surface pressure distribution and the predicted base pressure. The resultant additional loss includes all kinds of losses associated with incoming wakes, such as mixing loss of incoming wakes enhanced in the blade passage and unsteady interaction loss between incoming wakes and surface boundary layers. It was demonstrated that in an unsteady flow condition, a substantial performance improvement was obtained in the entire Reynolds number range by applying the surface velocity distribution with no laminar separation to a low-solidity blade row.

Improvements in the Prediction of Steady and Unsteady Transition and Mixing in Low-Pressure Turbines by Means of Machine-Learnt Closures

Abstract In this article, novel machine-learnt transition and turbulence models are applied to the prediction of boundary-layer transition and wake mixing in a low-pressure turbine (LPT) cascade, including unsteady inflow cases with incoming wakes. A laminar kinetic energy (LKE) transport approach is employed as baseline transition framework. The application of the machine-learnt explicit algebraic Reynolds stress models (EARSMs) takes advantage of a zonal strategy based on a newly developed sensing function that allows automated wake demarcation. This work compares the performance of several approaches that are based on the application of improved transition models without machine learnt EARSMs, baseline transition model with EARSMs trained for improved wake mixing, and new transition and turbulence closures that are simultaneously developed in a fully coupled way and aimed at improving both transition and wake mixing predictions in LPTs. The investigation is carried out on a cascade of industrial footprint, representative of modern LPT bladings. First, the various modeling frameworks are evaluated, without bar wakes (steady conditions), over a wide range of Reynolds number values. Unsteady Reynolds-averaged Navier–Stokes (URANS) analyses have also been carried out to investigate the predictive capabilities of machine-learnt closures in the presence of incoming bar wakes. Reynolds-averaged Navier–Stokes (RANS)/URANS results are scrutinized against large eddy simulation (LES) calculations and experimental data. It will be demonstrated that machine-learnt EARSMs are capable of producing realistic wake mixing when simply applied on top of the baseline transition models. However, the most accurate predictions will be shown to be provided by fully integrated machine-learnt transition/turbulence closures.

Numerical Study of the Boundary Layer Separation of a Low‐Pressure Turbine Cascade at Different Incidence Angles

Modern low‐pressure turbine (LPT) pursues high blade loading to improve its efficiency while the possibility of boundary layer separation on the blades is still a challenging problem. The incidence angle is one of the main factors affecting the flow separation and laminar‐turbulent transition, which is of key importance for the design of LPT. In this work, based on the initial simulation results obtained using the Reynolds‐averaged Navier–Stokes (RANS) method, the flow past a single LPT cascade at three representative incident angles (i = −10°, 0°, +10°) is investigated using large‐eddy simulation (LES) method with approximately 26 million structured grids. The simulations are carried out with Open Source Field Operation and Manipulation (OpenFOAM) for an off‐design low Reynolds number condition Re = 40,000 and Ma = 0.5. The time‐averaged aerodynamic performances and three‐dimensional instantaneous flow characteristics of the LPT cascade are discussed in detail, and the results show that the blade loading and the transverse pressure gradient (TPG) from the pressure side to the suction side of leading edge (LE) increase with increasing incidence angle. At the incidence angle of +10°, the LPT cascade undergoes separation and reattachment from the LE to around 20% Cax on the suction surface, which weakens the separation phenomenon at the rear half of the suction surface and the total pressure loss downstream of the trailing edge (TE). It is worth noting that the RANS method underpredicts the blade boundary layer separation region compared with LES under these extreme conditions. These results may offer off‐design condition data for the future improvement of RANS models or experimental studies.

Flow mechanism of a highly loaded low pressure turbine cascade with integrated-optimized end wall contouring and root lean

The end wall loss of modern highly loaded low pressure turbine (LPT) has been greatly increased, due to the enhanced secondary flow loss and boundary layer separation loss. Thus, it is of great significance to develop effective flow control strategies to improve the end wall flow condition and aerodynamic performance of modern LPT. This research carried out a numerical investigation on the coupled flow control strategy, which combined non-axisymmetric end wall contouring (NEC) and root tangential lean (RTL), based on a highly loaded LPT cascade (Zweifel = 1.59). Meanwhile, the optimization process was used to get the optimal design parameters of the coupled method NEC&RTL. The results indicate that the optimal coupled configuration can reduce the total pressure loss coefficient by 12.68% and the non-dimensional secondary kinetic energy by 23.91%. Compared with the reference cascade without modification, the coupled method is found to improve the end wall flow conditions: the passage vortex is weakened both in size and strength, mainly attributed to the smaller cross-passage pressure gradient resulting from NEC; the closed separation bubble near end wall and the three-dimensional separation flow before trailing edge are eliminated, due to the great downward pressure gradient near end wall resulting from RTL; and the counter vortex is eliminated and the slender back flow is weakened under the additional coupling flow control effect of NEC&RTL. Therefore, the coupled flow control method can not only highlight the advantages of the independent methods, but also induce external flow control superiorities, demonstrating the application prospect of the coupled flow control strategy on the highly loaded LPT.

Particle Image Velocimetry Measurements in a High-Speed Low-Reynolds Low-Pressure Turbine Cascade

Abstract Particle image velocimetry (PIV) measurements in the blade-to-blade (B2B) plane and cascade outlet plane (COP) of a high-speed low-pressure turbine (LPT) cascade were performed at engine-representative outlet Mach number (0.70–0.95), and Reynolds number (70–120 k) under steady flow conditions. The freestream turbulence characteristics were imposed by means of a passive turbulence grid. The PIV results on the B2B plane were compared against five-hole probe (5HP) and Reynolds-averaged Navier–Stokes (RANS) computations to assess the validity of measurement and simulation techniques in the engine-relevant LPT cascade flows. The PIV captured the wake depth and width measured by the 5HP whereas the RANS displayed an overprediction of the wake Mach number deficit. The 5HP was found to impose sinewave fluctuations of the measured flow angle downstream, around three times higher than PIV. Additionally, PIV estimated turbulence intensity (TI) in the cascade, showing TI decay along a streamline. At the highest Mach number, a peak TI occurred past a shock wave. Measurements of the outlet flow field highlighted a high TI in the secondary flow region whereas high degree of anisotropy (DA) was registered in the boundary of the secondary flow and freestream regions. The contribution of the streamwise fluctuation component was found to be less than the crosswise and radial components in the freestream region. Increasing the cascade outlet Mach number, the contribution of streamwise fluctuation to the DA was observed to decrease.

Aerodynamic Uncertainty Quantification of a Low-Pressure Turbine Cascade by an Adaptive Gaussian Process

Stochastic variations of the operation conditions and the resultant variations of the aerodynamic performance in Low-Pressure Turbine (LPT) can often be found. This paper studies the aerodynamic performance impact of the uncertain variations of flow parameters, including inlet total pressure, inlet flow angle, and turbulence intensity for an LPT cascade. Flow simulations by solving the Reynolds-averaged Navier–Stokes equations, the SST turbulence model, and γ−Re˜θt transition model equations are first carried out. Then, a Gaussian process (GP) based on an adaptive sampling technique is introduced. The accuracy of adaptive GP (ADGP) is proven to be high through a function experiment. Using ADGP, the uncertainty propagation models between the performance parameters, including total pressure-loss coefficient, outlet flow angle, Zweifel number, and the uncertain inlet flow parameters, are established. Finally, using the propagation models, uncertainty quantifications of the performance changes are conducted. The results demonstrate that the total pressure-loss coefficient and Zweifel number are sensitive to uncertainties, while the outlet flow angle is almost insensitive. Statistical analysis of the flow field by direct Monte Carlo simulation (MCS) shows that flow transition on the suction side and viscous shear stress are rather sensitive to uncertainties. Moreover, Sobol sensitivity analysis is carried out to specify the influence of each uncertainty on the performance changes in the turbine cascade.

Statistical investigations of profile error impact on flow and performance of a low-pressure turbine cascade

Profile error impacts on turbomachinery flow and blade performance have been attracting widespread attention. In the study, the characteristics of profile error of about one thousand real low-pressure turbine blades are extracted. Sensitivities of total pressure loss coefficient (ζ), outflow angle (β), and Zweifel lift coefficient (zw) of the blade to the basis modes of profile error are calculated. Flow solutions of the blades considering specified basis modes with high sensitivities illustrate that profile error contributes much to the variations of transition onset and flow acceleration on the suction side and flow mixing intensity in the wake. Uncertainty quantification of performance changes is then implemented by the method of moment (MM) using second-order sensitivities. With only 5% computational cost of that by Monte Carlo simulation (MCS), the MM-based statistical results are close to MCS ones with maximum relative error not exceeding 1.07%. The statistical results reveal that the variations of both β and zw are linearly dependent, whereas the variation of ζ is nonlinearly dependent on profile error. As the variation range of profile error increases, the standard deviation and skewness increase, indicating that the performance is more dispersive and the nonlinear dependence of ζ on profile error is intensified. Finally, the MCS flow fields are analyzed. Statistical shear stress near the leading edge and transition onset, statistical boundary layer momentum thickness near transition onset, statistical intermittency near transition onset, and statistical entropy in the wake are more considerable. The impact mechanisms of profile error on turbine flow and performance changes are demonstrated.

Assessment of the DDES-γ Model for the Simulation of a Highly Loaded Turbine Cascade

Abstract The flow over the linear low-pressure turbine cascade MTU-T161 at Re = 90,000 is analyzed using delayed detached eddy simulations (DDES). At this operating point, the low Reynolds number and the high loading of the blade result in a separation bubble and a separation-induced transition of the flow over the suction side. The utilized DDES method is based on a vorticity-based formulation to calculate the subgrid length scales, and it incorporates the one-equation γ-transition model. The computational model of the MTU-T161 cascade consists of one blade passage, including the diverging viscous sidewalls. To reproduce realistic operating conditions and to mimic the experiments, synthetic turbulence is prescribed at the inlet of the computational domain. Several studies are performed to assess the accuracy and performance of the DDES one-equation γ-transition model against experimental data and a benchmark large eddy simulations (LES). The primary focus is on the prediction of the separation and the separation-induced transition mechanism. First of all, a systematic grid convergence study is conducted and grid criteria are derived in order to ensure a satisfactory agreement of the flow metrics, such as isentropic Mach number, friction coefficient distribution, and total pressure wake losses at mid-span with experimental data. Furthermore, a detailed analysis of the DDES model parameters, such as shielding function and subgrid length scale, is presented and the effect of these parameters on the prediction accuracy of the separation bubble region is analyzed. The analysis of the suction side boundary layer indicates that the turbulent kinetic energy should be resolved and modeled properly in order to represent the separation bubble correctly. In particular, the correct prediction of the separated shear layer above the separation bubble is of utmost importance. The results of the simulations reveal higher demands on grid resolution for such transitional flows than typically have been reported in the literature for turbulent boundary layers. This higher demand on grid resolution results in more expensive simulations than Reynolds-averaged Navier–Stokes (RANS). Nevertheless, DDES requires less computing time than wall-resolved LES. Additionally, the results of the transitional DDES model are compared to DDES without a transition model, an RANS eddy viscosity model, and a reference LES. The results show that the DDES approach needs to be coupled with a transition model, such as the one-equation γ-transition model, in order to capture the flow topology over a highly loaded turbine blade correctly. The benefit of the DDES one-equation γ-transition model becomes particularly evident when predicting the separated shear layer, the transition process, and the subsequent reattachment. The RANS eddy viscosity turbulence and transition models applied within our study are not able to predict the aforementioned mechanisms accurately. For highly loaded turbine blades in particular, the accurate prediction of flow separation and potential reattachment is crucial for the aerodynamic design of turbines, since large parts of the total pressure loss are generated in the separated region. For this reason, the DDES one-equation γ-transition model can be a good compromise in terms of predictive accuracy and computational costs.

Time-Averaged Aerodynamics of a High-Speed Low-Pressure Turbine Cascade With Cavity Purge and Unsteady Wakes

Abstract The time-averaged aerodynamics of a high-speed low-pressure turbine (LPT) cascade were investigated under the impact of unsteady wakes and purge flows. The tests were performed at an outlet Mach (M) and Reynolds numbers (Re) of 0.90 and 70 k, respectively. Unsteady wakes were simulated by means of a spoked-wheel type wake generator (WG), and a reduced frequency of 0.95 was achieved. The development of a purge flow system to operate at low-pressure levels is presented alongside guidelines for the operation of the circuit. The new purge system was commissioned in terms of its long-term stability and flow uniformity at the cascade inlet. The impact of varying purge flows from a cavity versus a flat endwall was assessed by means of static pressure measurements on the blade pressure side (PS) and suction side (SS) and traverses performed downstream with a miniaturized multi-hole probe. Differences in the secondary flow structures resultant from injecting purge flow into the flowfield are observed, namely, the intensification of the trailing shed vortex (TSV) and passage vortex (PV) that is also displaced away from the endwall. An increase of the endwall losses occurs as the flat endwall was replaced with a cavity geometry and the cavity purge flowrate increases.

RANS Prediction of Losses and Transition Onset in a High-Speed Low-Pressure Turbine Cascade

Current trends in aero-engine design are oriented at designing high-lift low-pressure turbine blades to reduce engine weight and dimensions. Therefore, the validation of numerical methods able to correctly capture the boundary layer transition at cruise conditions with a steady inflow for high-speed blades is of great relevance for turbine designers. The present paper details numerical simulations of a novel open-access high-speed low-pressure turbine test case that are performed using RANS-based transition models. The test case is the SPLEEN C1 cascade, tested in transonic conditions at the von Karman Institute for Fluid Dynamics. Both physics-based and correlation-based transition models are employed to predict blade loading, boundary layer characteristics, and wake development. 2D simulations are run for a wide range of operating conditions ranging from low to high transonic Mach numbers (0.7–0.95) and from low to moderate Reynolds numbers (70,000–120,000). The γ-Re˜θt transition model shows a good performance over the whole range of simulated operating conditions, thus demonstrating a good capability in both reproducing blade loading and average losses, although the wake’s width is underestimated. This leads to an overestimation of the total pressure deficit in the center of the wake which can exceed experimental measurements by more than 50%. On the other hand, the k-ν2-ω model achieves satisfactory results at Ma6,is = 0.95, where the boundary layer state is affected by the presence of a weak shock impinging on the blade suction side which thickens the boundary layer, leading to a predicted shape factor equal to five, downstream of the shock. However, at low and moderate Mach numbers, the k-ν2-ω model predicts long or open separation bubbles contrary to the experimental findings, thus indicating insufficient turbulence production downstream of the boundary layer separation. The slow boundary layer transition in the aft region of the suction side that is exhibited by the k-ν2-ω model also affects the prediction of the outlet flow, featuring large peaks of a total pressure deficit if compared to both the experimental measurements and the γ-Re˜θt predictions. For the k-ν2-ω model, the maximum overestimation of the total pressure deficit is approximately 60%.

Compressibility effects on the flow past a T106A low-pressure turbine cascade

The present numerical investigation delves into the intricate interplay between Mach number (Ms), flow characteristics, and vorticity dynamics within a T106A low-pressure turbine (LPT) blade passage. The two-dimensional (2D) compressible Navier–Stokes equations are solved using a high-accuracy, dispersion relation preserving methodology, which is validated against benchmark direct numerical simulations. Four Ms ranging from 0.15 to 0.30 are computed in order to display the intricate response of compressibility on the separation-induced transition process. The emergence and evolution of unsteady separation bubbles along the suction surface of the T106A blade are explored, revealing a growing trend with Ms. The time-averaged boundary layer parameters evaluated along the suction surface display a delayed separation with a smaller streamwise extent with increasing Ms. However, an overall increase in the blade profile loss and a decrease in turbulent mixing are observed with increasing Ms, suggesting a detrimental effect on LPT performance. Applying the compressible enstrophy transport equation (CETE) to the flow in a T106A blade passage reveals that while a linear relationship exists between Ms and certain CETE budget terms, other terms have a nuanced dependency, which paves the way for future investigations into the role of compressibility on enstrophy dynamics.

Impact of Unsteady Wakes on the Secondary Flows of a High-Speed Low-Pressure Turbine Cascade

The aerodynamics of a high-speed low-pressure turbine (LPT) cascade were investigated under steady and unsteady inlet flows. The tests were performed at outlet Mach (M) and Reynolds numbers (Re) of 0.90 and 70k, respectively. Unsteady wakes were simulated by means of a wake generator equipped with bars. A bar reduced frequency (f+) of ∼0.95 was used for the unsteady case. The inlet flow field was characterized in terms of the total pressure profile and incidence. The blade aerodynamics at midspan and the secondary flow region were investigated by means of pneumatic taps and hot-film sensors. The latter provided a novel view into the impact of the secondary flows on the heat transfer topology on the blade suction side (SS). The cascade performance was quantified in terms of the outlet flow angle and losses by means of a directional multi-hole probe. The results report the phase-averaged impact of unsteady wakes on the secondary flow structures in an open test case high-speed LPT geometry.