Cascade Flow Research Articles

Experimental study on multi-angle pulsed jet actuators for controlling corner separation flow in a compressor cascade

Three-dimensional corner separation caused by the aerodynamic design of high-load compressor cascades is the main factor that limits their performance enhancement. Because of the unsteady characteristics of large-scale flow separation, injecting unsteady jets into the flow field has become a new flow control method. In this study, the essential flow characteristics of a compressor cascade were obtained through numerical simulations. Subsequently, the effect of pulsed jet angle on the aerodynamic performance of the cascade was experimentally investigated under different operating conditions using pulsed jet actuators. The results showed that at the design incidence angle of 0° and near-stall incidence angle of +4°, the starting point of the corner separation is located at 21 % and 9 % of the axial blade chord, respectively. The pulsation frequency downstream of the cascade trailing edge is 1454.5 Hz. Under the design conditions, the 20° pulsed jet exhibits the best control effect, reducing the total pressure loss coefficient by 13.4 % compared with that of the original cascade. Moreover, pulsed jets demonstrate strong applicability under variable operating conditions. At near-stall incidence angles, when the jet angle is 30°, the loss-reduction ability of the pulsed jet is maximized, decreasing the loss by 25.2 %. Pulsed jets reduce the cascade loss primarily by suppressing the secondary flow at the endwall and discretizing the vortex structures in the channel.

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.

A Rapid RI-TP Model for Predicting Turbine Wake Interaction Broadband Noise

Future UHBR (Ultra-High Bypass-Ratio) engines might cause serious ‘turbine noise storms’ but, at present, turbine noise prediction capability is lacking. The large turning angle of the turbine blade is the first major factor deserving special attention. The RANS (Reynold Averaged Navier–Stokes equation)-informed (here called RI) method and LINSUB (the bound vorticity 2D model LINearized SUBsonic flow in cascade), developed to predict fan broadband noise, coupled with a two-flat-plates (here called TP) assumption for the turbine blade, is applied here, and one autonomous rapid RI-TP model for predicting turbine wake interaction broadband noise has been developed. Firstly, taking the single axial turbine test rig NPU-Turb as the object, both the experimental data and the DDES/AA (delayed Detached Eddy Simulation/Acoustic Analogy) hybrid model have been used to validate the RI-TP model. High consistency in the medium and high frequencies among the three designed and off-designed rotation speeds indicates that the RI-TP model has the ability to predict turbine broadband noise rapidly. And compared with the original RANS-informed method, with one thin-flat-plate assumption on the blade, the RI-TP model can enhance the PWL (sound power level) in almost the whole spectral range below 10 KHz, which, in turn, is closer to the experimental data and the DDES/AA prediction results. The PWL trend with a ‘dividing point’ position is also studied. The spectrum would move up or down if the location is away from true value. In addition, the extraction location for turbulence as an input for the RI-TP model is negligible. In the future, multi-stage characteristics and the blade thickness effect should be further considered when predicting turbine noise.

Effect of pressure-side tip winglet with different heights and lengths on clearance flow in a compressor cascade

The clearance flow influence law and mechanism of pressure tip winglets with different fusion heights and lengths are investigated by numerical simulation methods based on a compressor cascade to weaken compressor clearance leakage and improve cascade aerodynamic performance. The result demonstrates that the tip winglet can improve the spanwise pressure flow and narrow the tip separation range, thereby suppressing the intensity of the leakage vortex. The enhanced effect on the leakage vortex is more significant when the tip winglet's fusion length range can include the leakage vortex's initial position. In addition, narrower fusion heights and longer fusion lengths enhance the improvement effect. The tip winglet provides the most significant effect, reducing total pressure loss by 0.64% and leakage by 16.8% when the fusion height is 1% blade height and the length is the whole chord.

Investigation of Compressor Cascade Flow Using Physics-Informed Neural Networks with Adaptive Learning Strategy

In this study, we utilize the emerging physics-informed neural networks (PINNs) approach for the first time to predict the flowfield of a compressor cascade. Different from conventional training methods, a new adaptive learning strategy that mitigates gradient imbalance through incorporating adaptive weights in conjunction with a dynamically adjusting learning rate is used during the training process to improve the convergence of PINNs. The performance of PINNs is assessed here by solving both the forward and inverse problems. In the forward problem, by encapsulating the physical relations among relevant variables, PINNs demonstrate their effectiveness in accurately forecasting the compressor’s flowfield. PINNs also show obvious advantages over the traditional computational fluid dynamics (CFD) approaches, particularly in scenarios lacking complete boundary conditions, as is often the case in inverse engineering problems. PINNs successfully reconstruct the flowfield of the compressor cascade solely based on partial velocity vectors and near-wall pressure information. Furthermore, PINNs show robust performance in the environment of various levels of aleatory uncertainties stemming from labeled data. This research provides evidence that PINNs can offer turbomachinery designers an additional and promising option alongside the current dominant CFD methods.

Reduced-order prediction of unsteady spatial-temporal aerodynamics in a turbine cascade

A low-cost prediction method that effectively captures the detailed dynamics of unsteady motions is necessary for turbomachinery design. This paper applies two data-driven methods for unsteady cascade flow of a T106 low-pressure turbine with periodic incoming wakes under unknown conditions and unknown instants, respectively. For the prediction under unknown conditions, the dominant coherent structures of the unsteady flows are obtained using sparsity-promoting dynamic mode decomposition. An arbitrary case's sparse promoting modes serve as a basis for prediction and polynomial interpolation is employed to predict the characteristic parameters, including the amplitude and frequency. Based on the predicted characteristic parameters and sparse promoting modes, the flow fields within a range of Reynolds numbers can be reconstructed. The results show that the large-scale flow structure at different Reynolds numbers can be predicted with reasonable error. The detailed flow structure of cascade flow fields also agrees well with simulation results, demonstrating the method's excellent applicability. For the prediction under unknown instants, the dominant coherent structures of the unsteady flows are obtained using proper order decomposition. The extreme gradient boosting method is utilized to construct a surrogate model and predict the time coefficients at unknown times. Based on the dominating modes and predicted time coefficients, the flow fields within a range of unknown instants can be reconstructed. The cascade flow fields can be recovered with a relative error of less than 3 %. The vortex structures and blade surface pressure agree well with simulation results. The present work provides a promising approach for turbomachinery design and investigating underlying mechanisms with low data requirements.

Effect of moving end wall on tip leakage flow in a compressor cascade with different clearance heights

Numerical simulations have been carried out to investigate the effect of the moving end wall on the tip leakage flow structure in a compressor cascade with four different tip clearance heights. A detailed comparison of the leakage flow’s loss; mass flow rate; and the tip leakage vortex and its roll-up, trajectory, size, and interaction with the passage flow was made. The results show that the performance of the cascade changes more severely as the tip clearance height increases with the moving end wall than with the stationary end wall. The roll-up of the tip leakage vortex has been studied by analyzing the pathline structure and vorticity distribution. An alternative explanation is proposed for the initial roll-up mechanism of the tip leakage vortex. The vorticity transport is responsible for the initial roll-up of the vortex, whereas the leakage jet/passage flow shearing is responsible for the vortex development. The smaller the clearance height is, the easier it is for the moving end wall to alter the vorticity transport from the gap to the tip leakage vortex.

Power-loss methodology for a compressor cascade at various Reynolds numbers and its validation

Finding ways to identify and quantify the losses from various sources in turbomachinery is significant for understanding the physical loss mechanisms and improving aerodynamic performance. However, traditional loss-assessment methods fail to reveal the local losses and decouple the flow field. In this paper, a new power-loss methodology is proposed. This methodology defines local and accumulated power losses, and a new method of averaging the total outlet pressure is presented. This establishes a direct relationship between the well-known total pressure loss and the accumulated power loss. The method was verified based on experimental results, the Reynolds-averaged Navier–Stokes equations, and large-eddy simulations of a compressor cascade at various Reynolds numbers. By applying this method, the boundary-layer loss, separation loss, and trailing-edge mixing loss of the compressor cascade were successfully distinguished and quantitatively accounted for. The method has been shown to be a valuable tool for understanding and quantifying the losses experienced in different flow regimes. In conclusion, the power-loss methodology demonstrates the potential for accurate quantitative analysis of local and global loss generation, the investigation of physical mechanisms, and the development of physical models for diverse complex flows beyond just the compressor cascade flow.

Prediction of Transonic Flow over Cascades via Graph Embedding Methods on Large-Scale Point Clouds

In this research, we introduce a deep-learning-based framework designed for the prediction of transonic flow through a linear cascade utilizing large-scale point-cloud data. In our experimental cases, the predictions demonstrate a nearly four-fold speed improvement compared to traditional CFD calculations while maintaining a commendable level of accuracy. Taking advantage of a multilayer graph structure, the framework can extract both global and local information from the cascade flow field simultaneously and present prediction over unstructured data. In line with the results obtained from the test datasets, we conducted an in-depth analysis of the geometric attributes of the cascades reconstructed using our framework, considering adjustments made to the geometric information of the point cloud. We fine-tuned the input using 1603 data points and quantified the contribution of each point. The outcomes reveal that variations in the suction side of the cascade have a significantly more substantial influence on the field results compared to the pressure side and explain the way graph neural networks work for cascade flow-field prediction, enhancing the comprehension of graph-based flow-field prediction among developers and proves the potential of graph neural networks in flow-field prediction on large-scale point clouds and design.

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.

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.

An investigation comparing various numerical approaches for simulating the behaviour of condensing flows in steam nozzles and turbine cascades

The process of condensation takes place within the low-pressure stages of the steam turbine when undergoing rapid expansion. The dry supercooled steam turns into very tiny liquid droplets, and the resulting wet steam mixture causes additional losses and maintenance problems. Accurate simulation of steam condensing flows helps to obtain accurate information about the thermodynamics of such flows and use this information in the design of highly efficient steam turbine stages. In this study, by using the available numerical models in commercial CFD codes, seven cases are considered for simulating steam condensing flows. The important difference between these cases is the use of different condensation models and different equations of state to calculate the thermodynamic properties of wet steam. The objective of this research is to identify an appropriate model that can be used to simulate the flow of steam condensation effectively. In recent studies, it is still necessary for further improvement of the modelling methods because the numerical results did not fully match the experimental findings, underscoring the persisting uncertainties within this domain. The current study explores various condensation models and equations of state for calculating the thermodynamic properties of wet steam. This diversity of approaches is novel and allows for the comparison of different models to determine the most suitable one for effective flow simulation. The geometries of the IWSEP nozzle (International Wet Steam Experimental Project) and linear cascade of the last-stage rotor blades were considered. To identify the most appropriate model for the simulation of steam condensing flows, the numerical results are validated against in-house experiments. The results indicate that combining the Young droplet growth model with the Vukalovich and Young equations in cases 1 and 2 is not a suitable method for modelling steam condensing flows. However, cases 3 & 4, which are the combination of Gyarmathy and Fuchs-Sutugin droplet growth models with NIST real gas models, are the most appropriate ones. The findings of this research confirm the high sensitivity of the modelling of such flows, and emphasize that the necessary care should be taken in choosing the appropriate numerical model.

Primary aluminum-air flow battery for high-power applications: Optimization of power and self-discharge

Aluminum-air batteries are a front-runner technology in applications requiring a primary energy source. Aluminum-air flow batteries have many advantages, such as high energy density, low price, and recyclability. One of the main challenges with aluminum-air batteries is achieving high power while parasitic corrosion and self-discharge are minimized. In this study, the optimization of an aluminum-air flow cell by multiple-parameters analysis and integration of a four-cell stack are shown. We also studied the incorporation of ammonium metavanadate (NH4VO3) as anticorrosive in 4 mol L-1 KOH electrolyte by discharge and polarization plots. It was concluded that NH4VO3 is an efficient anticorrosive at low currents, but it limits the battery reaction at high-current and high-power applications. Nevertheless, high currents inhibit the corrosion reaction using 4 mol L-1 KOH electrolyte, allowing high power and capacity without anticorrosive additives. The flow in the stack also plays a significant role, and parallel flow is suggested over cascade flow since the latter results in the progressive accumulation of hydrogen as the electrolyte flows through the stack.

Partially saturated granular flow in a rotating drum: The role of cohesion

Partially saturated granular flows are common in various natural and industrial processes, such as landslides, mineral handling, and food processing. We conduct experiments and apply the discrete element method to study granular flows in rotating drums under partially saturated conditions. We focus on varying the strength of cohesion (surface tension) and rotation rate within the modes of rolling flow and cascading flow. With an increase in surface tension, a rolling mode can possess a steeper slope and correspondingly needs a higher rotation rate to transition to a cascading. The depth of the flowing region increases with increasing cohesion, while the sensitivity is reduced for cases of high cohesion. We propose a dimensionless number CE that captures the combined effects of rotation, gravity, and cohesion on the dynamic angle of repose and flow depth. In addition, we extract statistical information on the formation of clusters within the flow. We find a power law relation between the cluster size distribution and its probability, which indicates that stronger cohesion can promote the formation of larger clusters, and we discuss how cohesion impact on flows manifested by cluster formation.

Research on time sequence prediction of supersonic cascade flow field based on compressed sensing artificial neural network

The aviation engine that achieves efficient energy conversion is the core power equipment for low-carbon navigation, and the thermal components represented by the combustion chamber greatly affect the stable state of the compressor cascade flow field. Accurate, comprehensive and promptly monitoring of the compressor cascade flow state is related to the safe operation of the engine. A flow field time sequence prediction framework named compressed convolutional gate recurrent unit (CC-GRU) was proposed in this study to predict future supersonic cascade flow parameters based on the flow field at previous moments. CC-GRU embedded convolution into gate recurrent unit (GRU) to deal with the complex spatial-temporal behavior of supersonic cascade flow field. Firstly, unsteady numerical simulations driven by linear changes in back pressure were carried out, and the dataset for model training and validation was obtained to verify the feasibility of time sequence prediction of the cascade flow field. The verification results indicate that the framework can comprehensively predict the flow field with high back pressure in the future according to the flow field with low back pressure in the past period, and further validated the effectiveness of the proposed time sequence prediction model in ground wind tunnel experiments. The CC-GRU model can accurately capture the fine shock wave structure and flow separation zone, with a relative error of less than 10% in predicting the pressure field, and is mainly concentrated within the shock wave structure. Therefore, this research provides new research perspective and technical support for comprehensive and promptly condition monitoring of supersonic cascade flow field.

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.

Preliminary Numerical Study of a Rectilinear Blade Cascade Flow for a Determination of Aerodynamic Characteristics

Preliminary Numerical Study of a Rectilinear Blade Cascade Flow for a Determination of Aerodynamic Characteristics

Heavy quasiparticles and cascades without symmetry breaking in twisted bilayer graphene

Among the variety of correlated states exhibited by twisted bilayer graphene, cascades in the spectroscopic properties and in the electronic compressibility occur over larger ranges of energy, twist angle and temperature compared to other effects. This suggests a hierarchy of phenomena. Using a combined dynamical mean-field theory and Hartree calculation, we show that the spectral weight reorganisation associated with the formation of local moments and heavy quasiparticles can explain the cascade of electronic resets without invoking symmetry breaking orders. The phenomena reproduced here include the cascade flow of spectral weight, the oscillations of remote band energies, and the asymmetric jumps of the inverse compressibility. We also predict a strong momentum differentiation in the incoherent spectral weight associated with the fragile topology of twisted bilayer graphene.

Sulfate-rich spring seeps and seasonal formation of terraced, crystalline mirabilite mounds along the shores of Great Salt Lake, Utah: Hydrologic and chemical expression during declining lake elevation

As Great Salt Lake (GSL) elevation declined below ∼1278.6 m (4195 ft) beginning in the fall of 2019, crystalline mounds formed on the southeastern shore, near Great Salt Lake State Park, Utah. Soon after, several more mound complexes were discovered on nearby Antelope Island. Recent historic low lake levels permitted sulfate-saturated spring brines to emerge on the exposed shoreline. When the spring waters encountered cold winter air, sodium sulfate precipitated in the form of the mineral mirabilite (Na2SO4·10H2O). Mirabilite-saturated spring waters pool in shallow sediment-collapse depressions or, with sufficient hydraulic head, precipitate subaerial crystalline spring terraced mounds. The mounds are composed of clear, bladed, and tabular mirabilite crystals (1 to 10 cm in length; 1 to 5 cm in width) that form mini pools and rimstone dams due to cascading spring water flow. The waters have elavated μM concentrations of sulfide, an oxidation-reduction potential (ORP) of −250 mV, pH of 7, densities of 1.103–1.1169 g/cm3, and temperatures of 10°–15 °C, as compared to nearby lake waters that had undetectable sulfide, an ORP of 12 mV, pH of 8.2, density of 1.0872 g/cm3, and temperatures of 0°–3 °C. Green algae and probable sulfide oxidizing bacteria thrive in the spring waters and some are occluded within the mirabilite matrix and fluid inclusions. Sulfur δ34S and oxygen δ18O isotopes of brine and mirabilite sulfate are enriched +18.8–20.41‰ and + 12.2–14.5‰, respectively, indicating groundwater and mirabilite are in equilibrium for oxygen. Brine sulfide is heavily fractionated (δ 34S of ∼ − 30 ‰) relative to sulfate, indicating active sulfate reduction in subsurface aquifers that feed the spring seeps and which is consistent with higher HS− concentrations relative to adjacent lake waters. The recognition of such biosignatures retained in mirabilite provides further insights for the preservation potential of biological material in extraterrestrial sulfate minerals.Today, Gilbert Bay (south arm of GSL) is undersaturated with respect to mirabilite. However, pre-earthen causeway historical reports (prior to 1959) indicate mirabilite precipitated in the south arm during the winter and through wave action accumulated along the leeward southeastern oolitic shore (similar to current processes occurring in the hypersaline Gunnison Bay, the north arm of GSL). Upon solar irradiance in the spring, the shoreline mirabilite dissolved and reprecipitated in the shallow subsurface (<1 m) as an ooid cement. We hypothesize that this subsurface layer of mirabilite is the source for active lake margin sodium sulfate-saturated spring brines. The emergence and surface exposure of the brines and associated chemical sediments are an additional contributing solute source that may increase GSL salinity during lake level decline more than evaporation alone.

Optimization of inlet conditions of hot steam injection into the non-equilibrium condensing steam

Injecting hot steam into the cascade flow is one of the procedures for resisting losses and damages caused by condensation. In the current study, utilizing a 3D (three-dimensional) geometry for steam turbine blades, the hot steam has been injected into the steam cascade via the embedded channel. In the power plant industry, the hot steam injection process is done in two ways: constant pressure with a reservoir or constant mass flow rate utilizing a control valve. Therefore, considering these two methods and the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) optimization method, the best temperature for injecting hot steam into non-equilibrium steam in a constant steam turbine blade has been gained. At the optimal temperature of 540 K at the constant pressure mode, Er (erosion rate ratio) and Lr (condensation loss ratio) were obtained as 66.6% and 30.7%, respectively, and Kr (kinetic energy ratio) showed a 0.6% growth in the hot steam injection mode, in comparison with the original mode. In addition, the economic cost of hot steam injection was calculated as 0.457 ($/hour). By the TOPSIS optimization method, the optimal temperature of hot steam injection, utilizing the constant mass flow rate method, has been obtained as 460 K, and the Er, Lr, and Kr values were 31.2%, 66.1%, and 88.48%, respectively at the optimal temperature. Moreover, the economic cost was 0.43 ($/hour). It is easier to control the steam injection by the constant mass flow rate method utilizing a control valve; therefore, the 460 K temperature and constant mass flow rate method are introduced as the optimal method.