Low Pressure Turbine Research Articles

Unsteady Interaction Between Purge Flow and Secondary Flow in High-Lift Low Pressure Turbine

Abstract The coupling effect between the complex vortex system and the rim purge flow in the endwall region of a high-lift low pressure turbine (LPT) will significantly influence the evolution of secondary flow and the corresponding losses. This paper focused on the unsteady interaction mechanism between the rim purge flow and the secondary flow inside the high-lift LPT under the periodic wake passing. The large eddy simulation (LES) method was used to reveal the influence mechanism of rim purge flow, rotor-stator cavity interaction and unsteady wakes on the secondary flow. Detailed experimental measurement was carried out for the flow field of high-lift LPT under the influences of static purge flow. The results showed that the rim purge flow significantly increased the overturning and underturning downstream of the endwall region, resulting in aggravating secondary loss. The rotating-rim increased the difference of the circumferential velocity between the mainstream and the purge flow, aggravating the Kelvin-Helmholtz (K-H) instability, inducing the K-H vortex structure with stronger energy amplitude, and further increasing the endwall flow loss. The incoming wakes weakened the energy amplitude of the K-H vortex at the rim purge outlet, thinned the thickness of the low-energy fluid at the blade leading edge. Additionally, the interaction between the wakes and the secondary vortices further suppressed the development of the secondary flow. Nevertheless, the incoming wakes caused additional mixing losses and made a negative impact on the overall aerodynamic performance of the high-lift LPT.

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.

Impact of harmonic inflow variations on the size and dynamics of the separated flow over a bump

The separated flow over a wall-mounted bump geometry under harmonic oscillations of the inflow stream is investigated with direct numerical simulations. The bump geometry gives rise to streamwise pressure gradients similar to those encountered on the suction side of low-pressure turbine (LPT) blades. Under steady inflow conditions, the separated-flow laminar-to-turbulent transition is initiated by self-sustained vortex shedding due to Kelvin-Helmholtz (KH) instability. In LPTs the dynamics are further complicated by the passage of the wakes shed by the previous stage of blades. The wake-passing effect is modeled here by introducing a harmonic variation of the inflow conditions. Three inflow oscillation frequencies and three amplitudes are considered. The frequencies are comparable to the wake-passing frequencies in practical LPTs. The amplitudes range from 1% to 10% of the inflow total pressure. The dynamics of the separated flow are studied by isolating the flow components that are respectively coherent with and uncorrelated to the inflow oscillation. Three scenarios are identified. The first one is analogous to the steady inflow case. In the second one, the KH vortex shedding is replaced during a part of the inflow period by the formation and release of a large vortex cluster. The third scenario consists solely of the periodic formation and release of the vortex cluster; it leads to a consistent reduction of the separated flow length over the entire period compared to the steady inflow case and would be the most desirable flow condition in a practical application. Published by the American Physical Society 2024

LPT rotor speed after low-pressure shaft failure

When designing engine safety and compliance with airworthiness regulations, it is important to determine the variation of rotor rotational speed and other parameters of aero-engine under shaft failure scenarios. In this paper, a transient process simulation model is established using the component method for a high bypass ratio two-shaft direct-drive turbofan engine. It helps analyze the response of engine rotor speed and key temperature parameters after the failure of the low-pressure shaft, the influence of the fuel supply, low-pressure turbine efficiency, and rotor resistance torque on the response of the parameters. The results demonstrate that the sudden increase of the low-pressure shaft speed at the turbine end after the failure of the low-pressure shaft is the most important factor affecting the engine safety design. The fuel supply, LPT efficiency, and resistance torque have significant effects on this sudden increase in speed.

Research on Low Concentration Gas Catalytic Oxidation Power Generation System

In response to the difficulties in direct utilization of low concentration gas in coal mines and the slow development of industrial application of catalytic oxidation technology, a new mode of direct utilization of low concentration gas with a methane concentration of 1.0% in coal mines in catalytic oxidation gas turbine power generation is explored. And based on the development of a 30kW low concentration gas catalytic oxidation gas turbine power generation system, this paper introduces the design process of key equipment such as catalytic oxidation burners, low-temperature and low-pressure turbines, and countercurrent regenerators, providing a technical reference for the utilization of low concentration gas catalytic oxidation.

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°.

Mach number influence on low-pressure turbine flutter

The effect of the Mach number on the vibration amplitude trends of an isolated low-pressure turbine rotor is described. The study utilizes an analytical model correlating the aerodynamic work and the dry-friction work. Aerodynamic damping has been obtained using a frequency domain linearized Navier-Stokes solver, whereas friction damping has been modeled using a heuristic micro-slip model calibrated with the experimental data. In order to validate the analytical predictions, an extensive experimental campaign was conducted. Unsteady pressure transducers flushed mounted in the outer casing, one chord downstream of the trailing edge of the rotor, were used to characterize the vibration of the rotor. The analysis reveals a significant influence of the Mach number on the work balance between aerodynamic and mechanical components. It is observed that the vibration amplitude and the flutter-induced unsteady pressure perturbations of low-pressure turbine rotor blades notably increases when the exit Mach number does.

A ML strategy for the identification of optimal LPT design region and related blade shape

This work presents a machine-learning (ML) strategy for the identification of the design region that guarantees minimum losses for Low Pressure Turbine (LPT) blades, allowing the definition of the optimal blade shape. The data-driven procedure is twofold. Firstly, an advanced loss-correlation model (M1) that describes the LPT efficiency as a function of the main flow and geometrical parameters, also accounting for unsteady effects, has been trained from a numerical database. Then, a second model (M2) has been tuned to interpret the corresponding blade geometries. Proper Orthogonal Decomposition (POD) has been applied to formally decompose the blade shape into modes and coefficients. The modes provide basis functions, while the coefficients give the weights that, depending on the combination of the design parameters, define the blade shape. Gaussian Process (GP) and Cross-Validation techniques have been used for tuning both M1 and M2. Once properly tuned, the overall procedure provides the loss-correlation model (M1) for the identification of the design region that is expected to minimize losses, and the geometrical model (M2) for a quick definition of the corresponding optimal blade shape. The procedure can be extended to other engineering applications where own efficiency and geometrical data are available.

Unsteady Flows and Component Interaction in Turbomachinery

Unsteady component interaction represents a crucial topic in turbomachinery design and analysis. Combustor/turbine interaction is one of the most widely studied topics both using experimental and numerical methods due to the risk of failure of high-pressure turbine blades by unexpected deviation of hot flow trajectory and local heat transfer characteristics. Compressor/combustor interaction is also of interest since it has been demonstrated that, under certain conditions, a non-uniform flow field feeds the primary zone of the combustor where the high-pressure compressor blade passing frequency can be clearly individuated. At the integral scale, the relative motion between vanes and blades in compressor and turbine stages governs the aerothermal performance of the gas turbine, especially in the presence of shocks. At the inertial scale, high turbulence levels generated in the combustion chamber govern wall heat transfer in the high-pressure turbine stage, and wakes generated by low-pressure turbine vanes interact with separation bubbles at low-Reynolds conditions by suppressing them. The necessity to correctly analyze these phenomena obliges the scientific community, the industry, and public funding bodies to cooperate and continuously build new test rigs equipped with highly accurate instrumentation to account for real machine effects. In computational fluid dynamics, researchers developed fast and reliable methods to analyze unsteady blade-row interaction in the case of uneven blade count conditions as well as component interaction by using different closures for turbulence in each domain using high-performance computing. This research effort results in countless publications that contribute to unveiling the actual behavior of turbomachinery flow. However, the great number of publications also results in fragmented information that risks being useless in a practical situation. Therefore, it is useful to collect the most relevant outcomes and derive general conclusions that may help the design of next-gen turbomachines. In fact, the necessity to meet the emission limits defined by the Paris agreement in 2015 obliges the turbomachinery community to consider revolutionary cycles in which component interaction plays a crucial role. In the present paper, the authors try to summarize almost 40 years of experimental and numerical research in the component interaction field, aiming at both providing a comprehensive overview and defining the most relevant conclusions obtained in this demanding research field.

A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines

Abstract No common laminar kinetic energy (LKE) transition model has to date been able to predict both separation-induced and bypass transition, both phenomena commonly found in low-pressure turbines and high-pressure turbines. Here, a data-driven approach is adopted to develop a more general LKE transition model suitable for both transition modes. To achieve this, two strategies are adopted. The first is to extend the computational fluid dynamics (CFD)-driven model training framework for simultaneously training models on multiple turbine cases, subject to multiple objectives. By increasing the training data set, different transition modes can be considered. The second strategy employed is the use of a newly derived set of local non-dimensionalized variables as training inputs to reduce the search space. Because one of the training turbine cases is characterized by strong unsteady effects, for the first time an unsteady solver is utilized during the CFD-driven training, and the time-averaged results are used to calculate the cost function as part of the model development process. The results show that the data-driven models do perform better, in terms of their predictions of pressure coefficient, wall shear stress, and wake losses, than the baseline model. The models were then tested on two previously unseen testing cases, one at a higher Reynolds number and one with a different geometry. For both testing cases, stable solutions were obtained with results improved over the predictions using the baseline models.

Prediction of the Influence of the Inlet End-Wall Boundary Layer on the Secondary Flow of a Low Pressure Turbine Airfoil Using RANS and Large-Eddy Simulations

Abstract This paper analyzes the effect of the inlet end-wall boundary layer on the secondary flow of a low pressure turbine airfoil cascade at Reynolds number 2 × 105 using RANS and implicit large-eddy simulations (LES). The results are compared against experimental data obtained at two low-speed linear cascade facilities, one located at the Whittle Laboratory of the University of Cambridge and the other at the Polytechnic University of Madrid. The RANS turbulence model is the k−ω−γ−Reθt and no sub-grid scale model has been used in the LES. An unstructured mesh of hexahedra and prisms is used, with high order elements used in the boundary layer region to better describe the airfoil shape in the LES. Two inlet end-wall boundary layers that produce different secondary flow patterns are analyzed: a laminar thin velocity profile and a turbulent thick velocity profile with several inlet turbulent intensities. The agreement between LES numerical predictions and experimental measurements of the position and intensity of the secondary vortices is very good for both cases. RANS simulations are much cheaper in terms of computational cost and reasonably predict most of the flow features, except when the inlet turbulence is low and turbulent transition prediction becomes critical. The effect of the inlet velocity profiles and inlet turbulence on the secondary flow structure is quite pronounced. The velocity profile thickness determines the spanwise penetration of the passage vortex, and different inlet turbulence intensities modify its mixing. Higher inlet turbulence intensities lead to a decrease of the secondary losses due to the passage vortex and an increase of end-wall losses.

Flame-retardant mechanism of TiAl alloy by frictional ignition method

TiAl is used as the preferred material for aero-engine low-pressure turbine blades, which is also faced with similar problems of “Titanium fire” under long-term high temperature service conditions. In this paper, the micro-combustion behavior of TiAl is discussed. It is found that the flame-retardant of the TiAl alloy has better performance compared to that of TC11, TA11. In this regard, the higher content of Al and Nb is identified as the primary reason for the superior flame-retardant performance for TiAl alloy. Moreover, the segregation serves as a transport channel for atoms and entraps oxygen atoms during the process of extended combustion. The three-stage combustion model before deflagration is presented. Furthermore, the flame-retardant mechanism before and after deflagration is explained, highlighting the main reason behind the formation of the final morphology of the alloy after combustion.

An Investigation of Efficiency Issues in a Low-Pressure Steam Turbine Using Neural Modelling.

This study utilizes neural networks to detect and locate thermal anomalies in low-pressure steam turbines, some of which experienced a drop in efficiency. Standard approaches relying on expert knowledge or statistical methods struggled to identify the anomalous steam line due to difficulty in capturing nonlinear and weak relations in the presence of linear and strong ones. In this research, some inputs that linearly relate to outputs have been intentionally neglected. The remaining inputs have been used to train shallow feedforward or long short-term memory neural networks using measured data. The resulting models have been analyzed by Shapley additive explanations, which can determine the impact of individual inputs or model features on outputs. This analysis identified unexpected relations between lines that should not be connected. Subsequently, during periodic plant shutdown, a leak was discovered in the indicated line.

Low cycle fatigue behavior and life prediction of a directionally solidified alloy

Low cycle fatigue behavior and life prediction of a directionally solidified alloy

Impact of High-Pressure-Turbine Purge Flow on the Evolution of Turbulence in a Turbine Vane Frame

Abstract This paper describes the measurement and postprocessing of turbulence data. The experiments were carried out in a two-stage, two-spool transonic turbine test rig at the Institute for Thermal Turbomachinery and Machine Dynamics at the Graz University of Technology, which includes relevant purge and turbine rotor tip leakage flows. The test setup consists of a high-pressure turbine (HPT) stage, a turbine vane frame (TVF) with turning struts and splitters, and a counter-rotating low-pressure turbine (LPT) to allow engine realistic measurements. Time-resolved area traverse measurements have been performed for three different operating conditions in three measurement planes downstream of the HPT rotor, which enable the measurement of the turbulence quantities at the TVF inlet and outlet as well as the LPT outlet. The turbulence quantities are evaluated using triaxial- and single hot-film probes by means of Constant-Temperature-Anemometry, and their results were validated with five-hole probe (FHP) measurements. Ensemble- and time-averaging, as well as Fourier transforms, were applied for data reduction. It is shown how the turbulence intensity and integral length scale vary over different purge flowrates (PFR). The acquired measurement data illustrate that the interaction of the ejected purge flow with mean flow enhances the turbulent mixing in the secondary flow structures at the TVF inlet and TVF outlet, respectively. Furthermore, the flow downstream of the LPT rotor is affected by TVF and LPT rotor secondary flow structures, which are identified as high turbulence regions. These regions strongly depend on the purge flowrate. These results acquired under engine realistic rig flow conditions enable a deeper understanding of the relationship between loss and turbulence quantities and will help improve the application of computational fluid dynamics turbulence models to turbomachinery modeling.

Study on high-altitude ceiling strategy of compression ignition aviation piston engines based on BP-NSGA II algorithm optimization

This paper explores the influence of different turbocharging modes and multi-parameter coordinated control on the performance of compression-ignition (CI) aviation piston engine (APE). Firstly, based on a constructed one-dimensional thermodynamic model of a CI APE, the study investigates the effects of different turbocharging modes and combinations of high and low-pressure stage variable geometry turbines (VGT) on the operational performance of the engine. Subsequently, a novel stepwise approximate multi-objective optimization algorithm is proposed, combining backpropagation neural networks and the non-dominated sorting genetic algorithm II. This algorithm evaluates the influence of multiple control parameters on a two-stage turbocharged engine's performance, achieving a balance between fuel economy and reliability. The research shows that equipping CI APEs with twin VGT for supercharging can notably enhance engine performance, enabling the achievement of favorable power recovery objectives at an altitude of 8000 m. The proposed optimization algorithm exhibits strong predictability and reliability, substantially accelerating the computation speed and reducing the data volume by approximately 95%. At an engine speed of 3887 rpm, compared to the unoptimized conditions, the brake specific fuel consumption of the best scenario at altitudes of 2000 m, 4000 m, 6000 m, and 8000 m is reduced by 7.1%, 7.2%, 8.6%, and 6.9%, respectively.

Stability of low-pressure turbine boundary layers under variable Reynolds number and pressure gradient

The free-stream turbulence induced transition occurring under typical low-pressure turbine flow conditions is investigated by comparing linear stability theory with wind tunnel measurements acquired over a flat plate subjected to high turbulence intensity. The analysis was carried out, accounting for three different Reynolds numbers and four different adverse pressure gradients. First, a non-similarity-based boundary layer (BL) solver was used to compute base flows and validated against pressure taps and particle image velocimetry (PIV) measurements. Successively, the optimal disturbances and their spatial transient growth were calculated by coupling classical linear stability theory and a direct-adjoint optimization procedure on all flow conditions considered. Linear stability results were compared with experimental particle image velocimetry measurements on both wall-normal and wall-parallel planes. Finally, the sensitivity of the disturbance spatial transient growth to the spanwise wavenumber of perturbations, the receptivity position, and the location where disturbance energy is maximized were investigated via the built numerical model. Overall, the optimal perturbations computed by linear stability theory show good agreement with the streaky structures surveyed in experiments. Interestingly, the energy growth of disturbances was found to be maximum for all the flow conditions examined, when perturbations entered the boundary layer close to the position where minimum pressure occurs.

Evaluation of a New Droplet Growth Model for Small Droplets in Condensing Steam Flows

As the condensation phenomenon occurs in the low-pressure stages of steam turbines, an accurate modelling of the condensing flows is very crucial and has a significant impact on the development of highly efficient steam turbines. In order to accurately simulate condensing steam flows, it is essential to choose the right condensation model. Further research to enhance condensation models is of special importance because the outcomes of numerical studies of condensation models in recent years have not been entirely compatible with the experiments and there are still uncertainties in this area. Therefore, the main aim of this paper is to evaluate a proposed droplet growth model for modelling condensation phenomenon in condensing steam flows. The new model is derived to profit from the advantages of models based on the continuum approach for large droplets and those based on the kinetic theorem for small droplets, which results in the model being robust for a wide range of Knudsen numbers. The model is implemented into a commercial CFD tool, ANSYS Fluent 2022 R1, using UDFs. The results of the CFD simulations are validated against experimental data for linear cascades within the rotor and stator blade geometries of low-pressure steam turbine stages. The findings clearly demonstrate the superiority of the new model in capturing droplet growth, particularly for very small droplets immediately following nucleation. In contrast, widely used alternative droplet growth models tend to either underpredict or overpredict the droplet growth rate. This research significantly contributes to the ongoing efforts to enhance condensation modeling, providing a more accurate tool for optimizing the design and operation of low-pressure steam turbines, ultimately leading to a higher energy efficiency and a reduced environmental impact.