Transonic Flow Field Research Articles

Placement of Recirculation Channel Casing Treatment in Transonic Fans: A Flow Physics Approach

This study investigates the effects of recirculation channel casing treatment positioning in a transonic fan. Recirculation channels are a passive casing treatment, consisting of an injection and extraction port connected by a secondary flowpath. Casing treatments typically extend stall margin at the cost of efficiency. However, in a transonic flowfield, strong pressure gradients can introduce an important unsteady component to the recirculation channel flow, giving these channels the potential to reduce this tradeoff by timing the injection and removal of the recirculated flow for maximum effectiveness. This timing aspect of the recirculation channel can be designed using the circumferential positioning (clocking) of the injection port relative to the extraction port. The presented results show two stability-enhancing mechanisms. First, the oscillation-attenuation mechanism improves flow stability by increasing the mean axial velocity at the tip and attenuating the oscillation of the shock and tip leakage vortex. Second, the tip leakage vortex (TLV) energization mechanism improves flow stability by injecting a jet that locally energizes the TLV. This study demonstrates that the stability-enhancing mechanism of the recirculation channel is determined by effective clocking.

Quantitative and Qualitative Experimental Assessment of Water Vapor Condensation in Atmospheric Air Transonic Flows in Convergent–Divergent Nozzles

Atmospheric air, being also a moist gas, is present as a working medium in various areas of technology, including the areas of airframe aerodynamics and turbomachinery. Issues related to the condensation of water vapor contained in atmospheric air have been intensively studied analytically, experimentally and numerically since the 1950s. An effort is made in this paper to present new, unique and complementary results of the experimental testing of moist air expansion in the de Laval nozzle. The results of the measurements, apart from the static pressure distribution on the nozzle wall and the images obtained using the Schlieren technique, additionally contain information regarding the quantity and quality of the condensate formed due to spontaneous condensation at the transition from the subsonic to the supersonic flow in the nozzle. The liquid phase was identified using the light extinction method (LEM). The experiments were performed for three geometries of convergent–divergent nozzles with different expansion rates of 3000, 2500 and 2000 s−1. It is shown that as the expansion rate increases, the phenomenon of water vapor spontaneous condensation appears closer to the critical cross-section of the nozzle. A study was performed of the impact of the air relative humidity and pollution on the process of condensation of the water vapor contained in the air. As indicated by the results, both these parameters have a significant effect on the flow field and the pressure distribution in the nozzle. The results of the experimental analyses show that in the case of the atmospheric air flow, in addition to the pressure, temperature and velocity, other parameters must also be taken into account as boundary parameters for possible numerical analyses. Omitting information about the air humidity and pollution can lead to incorrect results in numerical simulations of transonic flows of atmospheric air. The presented results of the measurements of the moist air transonic flow field are original and fill the research gap in the field of experimental studies on the phenomenon of water vapor spontaneous condensation.

Position query-guided cross-modal flow field prediction model of a transonic compressor cascade

The gradient of flow parameters in a transonic compressor cascade flow field varies significantly, especially in the region of shock waves, which causes a significant challenge to its high-precision flow field prediction. In this study, the position query-guided cross-modal flow field prediction model (PGCM) is proposed to effectively predict the flow field parameter distribution of a transonic compressor cascade. The PGCM utilizes the self-attention mechanism for the global and deep geometric feature extraction of configurations, which contributes to an in-depth understanding of the spatial relationships between coordinate points within the flow field, accurately capturing and analyzing the structural complexity of a compressor cascade flow. In addition, the PGCM integrates the cross-attention mechanism that establishes correlations between different input sequences, which enhances the performance of the model in querying and interpreting flow parameters at specific coordinates. The flow field prediction models are developed to predict the flow parameter distributions of different cascade geometries at Mach numbers of 0.78 and 0.93, respectively. The validation results indicate that the PGCM performs significantly better than the existing convolutional neural network and vision transformer, especially in the prediction of the pressure coefficient Cp distribution. The PGCM is adaptable to the variation of flow conditions and geometrical configurations efficiently and accurate in predicting the flow field of a compressor cascade. This paper demonstrates the promising potential of conducting the multi-modal information fusion to enhance the capability of flow field prediction.

Koopman neural operator approach to fast flow prediction of airfoil transonic buffet

Transonic buffet on airfoil is of great importance in the aerodynamic characteristics of aircraft. In the present work, a modified Koopman neural operator (KNO) is applied to predict flow fields during the transonic buffet process of the OAT15A [ONERA (National Office for Aerospace Studies and Research) Aerospatiale Transport aircraft 15 Airfoil] airfoil. Transonic buffet flow with different angles of attack is simulated by Reynolds averaged numerical simulation with the Menter's k−ω shear stress transport (SST) model at Reynolds number Re=3×106. A prediction model is directly constructed between the flow fields at several previous time nodes and that at the future time node by KNO. The predictions of flow fields with single sample and multi samples are performed to demonstrate the prediction accuracy and efficiency of KNO. The prediction of sequence flow fields based on the iterative prediction strategy is achieved for the transonic buffet process. The results indicate that KNO can achieve a fast and accurate prediction of flow physical quantities for the transonic buffet. Compared with other deep learning models including Unet and Fourier neural operator, KNO has a more advanced capability of predicting airfoil transonic buffet flow fields with higher accuracy and efficiency and less hardware requirements.

Transonic Flow Field Analysis of a Minimum Nozzle Length Rocket Engine

The aim of this paper is to develop a profile of axisymmetric minimum length nozzle giving a uniform and parallel flow at the exit section. The study is done at high temperature, lower than the dissociation threshold of the molecules. The design is made by the method of characteristics (MOC). The variation of the specific heats with the temperature is considered. The numerical results have been validated with CFD simulation Ansys-Fluent software. The second part of this study is to calculate and analyze the transonic flow field of this supersonic nozzle. The computation of the flow field characteristics at the throat is thus essential to the nozzle developed thrust value and therefore to the aircraft or rocket it propels. An investigation was conducted to analyze the effects of parameters on the position of the sonic line. These parameters include stagnation temperature T0, radius of the nozzle, types of gases, and exit Mach number ME.

Shock wave prediction in transonic flow fields using domain-informed probabilistic deep learning

Transonic flow fields are marked by shock waves of varying strength and location and are crucial for the aerodynamic design and optimization of high-speed transport aircraft. While deep learning methods offer the potential for predicting these fields, their deterministic outputs often lack predictive uncertainty. Moreover, their accuracy, especially near critical shock regions, needs better quantification. In this paper, we introduce a domain-informed probabilistic (DIP) deep learning framework tailored for predicting transonic flow fields with shock waves called DIP-ShockNet. This methodology utilizes Monte Carlo dropout to estimate predictive uncertainty and enhances flow-field predictions near the wall region by employing the inverse wall distance function-based input representation of the aerodynamic flow field. The obtained results are benchmarked against the signed distance function and the geometric mask input representations. The proposed framework further improves prediction accuracy in shock wave areas using a domain-informed loss function. To quantify the accuracy of our shock wave predictions, we developed metrics to assess errors in shock wave strength and location, achieving errors of 6.4% and 1%, respectively. Assessing the generalizability of our method, we tested it on different training sample sizes and compared it against the proper orthogonal decomposition (POD)-based reduced-order model (ROM). Our results indicate that DIP-ShockNet outperforms POD-ROM by 60% in predicting the complete transonic flow field.

Transonic flow field in critical flow Venturi nozzle

In this paper, theoretical and numerical analysis of a~transonic flow field of critical flow Venturi nozzles according to the ISO~9300 standard is performed. Deviations of the flow field from an estimate based on one dimensionality are clarified. While the theoretical analysis allows prediction of these deviations, the numerical analysis allows quantification of their influence. The main studied phenomena include the local supersonic compression in transonic expansion and the Prandtl-Meyer expansion. The tendency of the flow field to spatial oscillations is shown, alongside the ability of the system to damp these oscillations.

Numerical Simulation of Transonic Compressors with Different Turbulence Models

One of the most commonly used techniques in aerospace engineering is the RANS (Reynolds average Navier–Stokes) approach for calculating the transonic compressor flow field, where the accuracy of the computation is significantly affected by the turbulence model used. In this work, we use SA, SST, k-ɛ, and the PAFV turbulence model developed based on the side-biased mean fluctuations velocity and the mean strain rate tensor to numerically simulate the transonic compressor NASA Rotor 67 to evaluate the accuracy of turbulence modeling in numerical calculations of transonic compressors. The simulation results demonstrate that the four turbulence models are generally superior in the numerical computation of NASA Rotor 67, which essentially satisfies the requirements of the accuracy of engineering calculations; by comparing and analyzing the ability of the four turbulence models to predict the aerodynamic performance of transonic compressors and to capture the details of the flow inside the rotor. The errors of the Rotor 67 clogging flow rate calculated by the SA, SST, k-ɛ, and PAFV turbulence models with the experimental data are 0.9%, 0.8%, 0.7%, and 0.6%, respectively. The errors of the calculated peak efficiencies are 2.2%, 1.6%, 0.9%, and 4.9%. The SA and SST turbulence models were developed for the computational characteristics of the aerospace industry. Their computational stability is better and their outputs for Rotor 67 are comparable. The k-ɛ turbulence model calculates the pressure ratio and efficiency that are closest to the experimental data, but the computation of its details of the flow field near the wall surface is not ideal because the k-ɛ turbulence model cannot accurately capture the flow characteristics of the region of high shear stresses. The PAFV turbulence model has a better prediction of complex phenomena such as rotor internal shock wave location, shock–boundary layer interaction, etc., due to the use of a turbulent velocity scale in vector form, but the calculated rotor efficiency is small.

Manipulating near-wall flow instability and transport characteristics by the airfoil probe: Investigation on a transonic compressor cascade

The flow field exhibits complex features, such as shock waves, wakes, and end wall vortices in a transonic cascade. Installation of airfoil probes exacerbates the multi-scale and unsteady behavior of the internal passage flow. Apart from inducing measurement errors, it also generates extra flow loss inevitably and further affects the measuring accuracy. This paper investigates the impact of airfoil probes on a transonic compressor cascade's unsteady behavior and transport characteristics. Using high-fidelity numerical simulations, the influence of pipe layouts on the flow field of instrumented blades is visualized, revealing highly radial asymmetry. Loss analysis uncovers entropy transport induced by the streamwise vortices, primarily manifested by large-scale angular deformation at the outlet. The vortex structures in the wake region are dominated by momentum transport, displaying regional evolution and momentary equilibrium. The vortex expansion plays a leading role in the global vortex transport process, which is strengthened by the presence of the probes. Spatiotemporal analysis of the unsteady flow field can reveal some features overlooked by conventional fluid mechanics analysis. Using proper orthogonal decomposition, wake vortex pairs' high-frequency oscillations and shedding behaviors are captured in adjacent modes for the first time. The proposed approach can provide a theoretical basis for in-depth investigations of instrumented blade flow fields at the transonic regime. Furthermore, corresponding research can promote the refinement of instrument design by enabling experimentalists to understand the effects of intrusive instruments on transonic flow fields.

Research on transonic flow of nozzle contractions for providing an asymptotic solution

The effect of a contraction on the flow in a supersonic nozzle is investigated, and improvements are made to provide an accurate asymptotic solution of transonic flow. Owing to the elliptical characteristic of the governing equation, supersonic nozzle contractions are not rigorously designed from aerodynamics theory. The contraction effect is often masked by the design defects of the supersonic nozzle contours and, therefore, is hard to evaluate independently. In this study, the authors use a sufficiently advanced supersonic contour to support numerical and theoretical research on various contractions. The results show that the commonly used contractions lead to abrupt changes in transonic flow field parameters, and the degree does not vary with the nozzle Mach number. Based on the work of Hall, the accurate asymptotic solution of the sonic line in the nozzle is derived. Most practical sonic lines provided by various contractions are inconsistent with the accurate asymptotic solution, which further affects the uniformity of the supersonic flow. By iterating the shift of the Witoszynski contraction, the end point curvature is found to be the core parameter. On this basis, three improved contractions are proposed. These new contractions allow discontinuities in wall curvature and avoid the problem inherent in Sivells' cylindrical-quartic–conical-quartic contraction. Each improved contraction successfully coincides with theoretical transonic flow, helping the supersonic nozzle eliminate waves completely and achieve a high degree of flow uniformity.

Aerodynamic Load Reduction on a Supercritical Airfoil Using Tilted Microjets

Microjets arranged on the wing surfaces of civil transport aircraft have been shown to have great potential in suppressing high-frequency gust loads. This paper presents a study of aerodynamic load reduction on a supercritical airfoil using tilted microjets by solving the Reynolds-averaged Navier-Stokes (RANS) equations. The numerical method was first validated against the experimental and previous numerical data. Afterward, the subsonic and transonic flowfields around the supercritical airfoil were simulated with various angled microjets. The results show that both the lift reduction and the power efficiencies significantly increase as the blowing direction shifts downstream to upstream. The movement and weakening of the shock due to the jet are observed at α > 2 ∘ in transonic flow, resulting in a drag reduction compared to the baseline airfoil. However, the transient subsonic results revealed that the upstream jet induces a strong vortex shedding, which is suppressed in transonic flows. During jet deployment, there are three distinct phases: time lag, vortex rolling-up, and rebalancing, in that order. Once it reaches the trailing edge in subsonic flows, the starting vortex rapidly modifies the load and induced a strong roll-up vortex from the pressure surface. Nevertheless, in transonic flow, the rebalancing stage contributes to a greater reduction in lift due to the additional shock movement and weakening effect.

Fast transonic flow prediction enables efficient aerodynamic design

A deep learning framework is proposed for real-time transonic flow prediction. To capture the complex shock discontinuity of transonic flow, we introduce the residual network ResNet and deconvolutional neural networks to learn the nonlinear discontinuity phenomenon in transonic flow, which is affected by the Mach number, angle of attack, Reynolds number, and aerodynamic shape. In our framework, flow field variables on actual grid points are utilized in the neural network training to avoid the interpolation operation and the input of spatial position with a point cloud that is required with traditional convolutional neural networks. To investigate and validate the proposed framework, transonic flows around two-dimensional airfoils and three-dimensional wings are utilized to verify its effectiveness and prediction accuracy. The results prove that the model is able to efficiently learn the transonic flow field under the influence of the Mach number, angle of attack, Reynolds number, and aerodynamic shape. Significantly, some essential physical features, such as shock strength and location, flow separation, and the boundary layer, are accurately captured by this model. Furthermore, it is shown that our framework is able to make accurate predictions of the pressure distribution and aerodynamic coefficients. Thus, the present work provides an efficient and robust surrogate model for computational fluid dynamics simulation that enhances the efficiency of complex aerodynamic shape design optimization tasks and represents a step toward the realization of the digital twin concept.

Stall Margin Improvement in a Transonic Compressor With a Casing Treatment: Flow Mechanism

Abstract A compressor casing treatment with circumferential casing grooves (CCGs) is studied in detail. The primary objective of the current paper is to unearth the main driving fluid mechanism that changes the stall margin in a transonic compressor with CCGs. Large eddy simulation (LES) is applied to calculate the transonic compressor flow fields with and without CCGs. The present investigation shows that CCGs reduce the mass flow through the tip gap by about 16% near the stall condition. Calculated flow fields show that most of this reduction of tip leakage flow occurs near the CCGs. Reinjected flow from the CCGs pushes the tip leakage flow radially inward below the casing and changes how the tip leakage flow collides with the incoming main passage flow. However, a detailed examination of the calculated flow in the tip region shows that the reinjected flow does not contribute to the reduction of the overall blockage generation. The primary driver for reducing blockage generation with CCGs is the reduction of overall mass flowrate through the tip gap. In the present investigation, measurements show a very small decrease in efficiency with CCGs at the design flow condition, although the difference in efficiency is within the measurement uncertainty. Results from the LES simulation at the design condition with CCGs show that the tip leakage vortex (TLV) is pulled toward the blade suction side and double leakage flow is eliminated. The result is that the simulated efficiencies with and without CCGs are almost the same.

Using Tip Injection to Stability Enhancement of a Transonic Centrifugal Impeller with Inlet Distortion

This paper aims to understand the effects of circumferential inlet distortion and tip injection on a transonic impeller performance and flow field. For distorted inflow, the impeller is subjected to a stationary 120-degrees circumferential total pressure distortion. Full annulus unsteady three-dimensional analysis has been used to study the inlet distortion and tip injection effects on the impeller performance, stability and flow field. The results show that the circumferential inlet distortion reduces the impeller total pressure ratio and adiabatic efficiency; however, it has no significant impact on the safe operating range. Unlike the inlet distortion, the tip injection considerably increases the operating range. According to the results, the distortion and tip injection effect on the compressor performance is mainly due to changes in tip leakage flow. The inlet distortion has unfavorable influences on the flow field, especially near the impeller tip; however, the tip injection ameliorates the flow field in this region. In both the clean and distorted inflow, the tip injection causes downstream shock transmission, weakening the shock-tip leakage interaction. Hence, stall inception is postponed, and the impeller stability is improved in the presence of the tip injection.

An enhanced hybrid deep neural network reduced-order model for transonic buffet flow prediction

In the transonic flight environment, transonic buffet has significant influence on the aerodynamic characteristics of aircraft. In the face of the strong nonlinear characteristics of transonic buffet, the reduced-order model (ROM) technology based on deep learning (DL) is introduced to study the flow field. In this article, an enhanced hybrid deep neural network (eHDNN) consisting of Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (ConvLSTM) neural network is constructed as the ROM of unsteady transonic buffet flow field. By mining the spatial-temporal characteristic of buffet flow directly from large-scale flow field data, the eHDNN can predict complex flow characteristics such as shock wave motion in the unsteady buffet flow. Structural similarity information and nonlinear improvement strategies are introduced to improve the nonlinear expression ability of eHDNN. The predicted result is consistent with the numerical simulation and has high degree of prediction accuracy. In addition, the eHDNN has good generalization ability, which can predict the spatial-temporal evolution of buffet flow field at unknown angles of attack. The prediction method has good application prospect of the transonic buffet flow control and prediction, which also provides experience for DL modeling in other complex and strongly nonlinear flows.

A deep learning approach for the transonic flow field predictions around airfoils

Learning from data offers new opportunities for developing computational methods in research fields, such as fluid dynamics, which constantly accumulate a large amount of data. This study presents a deep learning approach for the transonic flow field predictions around airfoils. The physics of transonic flow is integrated into the neural network model by utilizing Reynolds-averaged Navier–Stokes (RANS) simulations. A detailed investigation on the performance of the model is made both qualitatively and quantitatively. The flow features associated with the transonic effects and the angle of attack variation, such as the shock waves and the flow separation, are well predicted. Furthermore, predicted flowfield data are used to compute the aerodynamic coefficients. The findings indicate that the presented model may allow avoiding time-consuming computational fluid dynamics (CFD) simulations, especially in the design optimization studies with a slight loss of accuracy.

Computation of three - dimensional transonic flow fields over a three - body launch vehicle configuration for low angle of attack conditions

The present work aims at the prediction of shock wave position on the heat shield region of a three body launch vehicle in transonic region. The launch vehicle consists of a cylindrical core body and two boosters. The core body is made of a spherical nose, followed by a cone and heat shield region which is a flat surface. The heat shield is followed by a boat tail. Simulations are performed with commercial CFD package, ANSYS –FLUENT. Reynolds stresses are computed using the k-ω SST turbulence model. Explicit time integration is used to obtain steady-state solutions. A structured grid over the vehicle is generated using ICEMCFD software. In the near-wall region of the launch vehicle fine mesh is employed to capture the boundary layer. Simulations are performed for angle of attacks (AOA) 0° and 4° for Mach number 0.95. The computed nose stagnation pressure compared with the isentropic relations and deviation found to be .067%. A standing normal shock wave is observed for AOA 0 whereas an oblique shock wave is observed for angle of attack 4°. The predicted flow structure in terms of density distribution is compared with experimental schlieren images. The predictions captured essential flow features such as expansion around the conical part, boundary layer over the heat shield, shock wave on the heat shield, and flow separation in the boat tail region. The predicted flow structure and shock wave position for AOA O matched well with the experiments. However, for AOA 4°, the deviation between flow structure and shock position is noticed. Possible reasons for the deviation are explained.

Investigation on flow field structure and aerodynamic load in vacuum tube transportation system

Vacuum Tube Transportation (VTT) system utilizes the low-pressure environment to achieve aerodynamic drag reduction and reduce the energy consumption of high-speed trains. Within this system, even for trains operating at subsonic speed, the flow acceleration around the streamlined train may leads to local supersonic flow. The appearance of the supersonic flow will dramatically alter the flow field structure and aerodynamic load of the high-speed train. Therefore, this study investigates two types of representative flow fields under different blockage ratio through the improved delayed detached eddy simulation (IDDES) method. The initialization, propagation, reflection and intersection process of shock waves in transonic case are captured and analyzed. It is shown that, the boundary layer thickness and width of vortex group in wake has experienced a slight increase with the increase of vacuum level. Compared with the subsonic case, the occurrence of choked flow and shock wave in transonic flow field lead to a decrease of wake region's vortex group width. As a result, the total drag coefficient of the train is increased by approximately one order of magnitude, and the dominant St number of tail car's drag coefficient has shifted from 0.16 to 0.11.

Experimental study on the rapid establishment of the transonic gap flow field

In turbine engines, there is a clearance between the rotating blade and the stationary casing. The flow in the tip gap, which is mostly transonic, has a significant impact on the overall thrust and safety performance of the engine. This study aims at elucidating the mechanism of flow establishment in a simplified tip gap model. In this study, the basic structure and pressure distribution of the transient flow field in the gap region are first determined via schlieren techniques and pressure measurements, respectively. Based on these results, we develop a rapid modeling technique of the flow field and analyze the similarities between gap flows with different aspect ratios. As demonstrated by this study, the gap flow can be established within 0.65 s and the entire process comprises five stages. The increase in the downstream pressure and relative fluid viscosity in the gap are found to significantly influence the shock wave structures. Similarities are observed between flow fields in different gaps when the width-to-height ratio is small. With a large width-to-height ratio, the viscosity of the fluid dominates and the corresponding flow fields exhibit no similarity.

跨音速流场测量楔形探针二维外形仿真研究

跨音速流场测量楔形探针二维外形仿真研究