Multistage Compressor Research Articles

Simulating Combined Cycle and Gas Turbine Power Plant under Design Condition using Open-Source Software DWSIM

Nowadays, clean and high-power generation is essential matters worldwide. To be improved and optimized, power plants require accurate models that can be introduced to process simulators. There is various commercial software for industrial simulation which is not accessible to everyone. The open-source DWSIM process simulator is the first chemical engineering code that offers many tools for the better study of industrial plants. In this paper, we employ DWSIM software to simulate a combined cycle gas turbine (CCGT) power plant under design conditions for three cases. The generic models are predicted for multistage compressors and compressor maps. In the first case, two models developed in ASPEN HYSYS and GateCycle will be considered. The achieved results by DWSIM are acceptably comparable for thermal efficiency and power generation. The DWSIM result is 3.5% lower than the ASPEN HYSYS for thermal efficiency, and the power generation is completely the same. In the second case, rigorous simulation was carried out using actual field data from the local CCGT power plant. The DWSIM outcomes are very close to the practical data. The power generation of GT and CC is very close; the variety is nearly 0.45%. In the third case, the simulation of CCGT with a cogeneration system is precisely accomplished, and the outcomes of DWSIM are shown in excellent agreement. The DWSIM prediction shows lower values by 0.26%, 4.79%, and 0.72% for the HP turbine, LP turbine, and plant net power, respectively.

The effects of the return channel geometry on the aerodynamic performance of a centrifugal compressor: A numerical study

In this paper, steady RANS (Reynolds-Averaged Navier-Stokes) numerical modeling of the return system of a centrifugal compressor is carried out to investigate the effects of various geometrical parameters on the aerodynamic performance of the return system. The effects of using splitter vanes in the return-channel, the width ratio of the return channel and the diverging angle of the walls are examined. Numerical results revealed that using splitter vanes can enhance the stage averaged pressure ratio and polytropic efficiency by 0.74 and 3.21%, respectively. Results showed that increasing the width ratio can enhance the efficiency and pressure ratio near the choke region, however, it has marginal effects on the performance at low flow coefficients. Results also showed that, due to the negligible effects of the diverging angle on the stage performance, using diverging hub wall can reduce the total axial length of the multistage compressor. Finally, a new return system is designed based on the combination of the best geometrical parameters found in the current study. Simulation results demonstrated that the average pressure ratio and efficiency of the compressor have been improved by 0.99% and 4%, respectively, by the newly developed return system compared to the original design.

Effects of Inlet Swirl Distortion on a Multi-Stage Compressor with Inlet Guide Vanes and Stall Margin Enhancement Method

Inlet swirl distortion is generally considered as a type of velocity distortion, and inlet guide vanes (IGVs) are widely used in the multi-stage compressor of aero-engines to eliminate the tangential velocity of the swirl flow. However, few studies have explored whether there still exists some negative influence of inlet swirl distortion on the compressor, even after the installation of IGVs. Therefore, in this study, the influence of various types of inlet swirl distortions on a multi-stage compressor with the installation of IGVs is investigated. A swirl distortion generator installed in the inlet duct was designed to produce various types of swirl flow patterns. When the distortion intensity increased to some degree, there still existed a decrease in the compressive capability and an obvious additional efficiency loss. The inlet twin swirl distortion was accompanied by total pressure distortion, so even with the installation of IGVs, there was still a significantly negative influence on the performance of the multi-stage compressor, especially the stall margin. Subsequently, to improve the stall margin under inlet swirl distortion, the stall precursor-suppressed (SPS) casing treatment was installed in the first stage of the multi-stage compressor. It could enhance the stall margin of the compressor with no obvious change in the characteristic curves and no additional efficiency loss under various types of inlet swirl distortions, and its mechanism was verified by capturing the dynamic pressure characteristics.

Predictive Maintenance and Fault Monitoring Enabled by Machine Learning: Experimental Analysis of a TA-48 Multistage Centrifugal Plant Compressor

In an increasingly competitive industrial world, the need to adapt to any change at any time has become a major necessity for every industry to remain competitive and survive in their environments. Industries are undergoing rapid and perpetual changes on several levels. Indeed, the latter requires companies to be more reactive and involved in their policies of continuous improvement in order to satisfy their customers and maximize the quantity and quality of production, while keeping the cost of production as low as possible. Reducing downtime is one of the major objectives of these industries of the future. This paper aimed to apply machine learning algorithms on a TA-48 multistage centrifugal compressor for failure prediction and remaining useful life (RUL), i.e., to reduce system downtime using a predictive maintenance (PdM) approach through the adoption of Industry 4.0 approaches. To achieve our goal, we followed the methodology of the predictive maintenance workflow that allows us to explore and process the data for the model training. Thus, a comparative study of different prediction algorithms was carried out to arrive at the final choice, which is based on the implementation of LSTM neural networks. In addition, its performance was improved as the data sets were fed and incremented. Finally, the model was deployed to allow operators to know the failure times of compressors and subsequently ensure minimum downtime rates by making decisions before failures occur.

Graphic Analytical Methods for Determining Moist Air Characteristics in Multistage Compressors

The purpose of the study is a comparative analysis of methods for graphic analytical determination of the characteristics of moist air in multistage compressors. Two methods are compared, which differ in the used I-d-diagrams: unified in terms of pressure and atmospheric. I-d-diagrams unified in terms of pressure differ from atmospheric ones by diagrams of saturated air relative humidity () only at various pressures. For multistage compressors, curves are plotted on unified I-d-diagrams at atmospheric pressure and compressed air pressure in intercoolers and receivers. It is assumed that the isobaric cooling of compressed air and condensation of its water vapor occurs in coolers and receivers at the final compression pressure in the previous compressor stages. The method, which uses I-d-diagrams unified by pressure, involves the diagram plotting of air compression and cooling on a grid of curves. An example of plotting such diagrams for a two-stage compressor with an intercooler and a receiver is given. A detailed description of the thermodynamic state of moist air in such a compressor is given. The nodal points of the processes in the compressor are plotted on a pressure-unified I-d-diagram according to the known values of moisture content and air temperature. The pressure and temperature at the end points of compression are calculated by the equations of the polytropic process at n = 1.26. The dew points in the cooler and receiver are graphically defined as the intersection of the curves for the final compression pressures with the corresponding straight lines for constant air moisture content in the compressor stages. The technique using atmospheric (barometric) I-d-diagrams is used in the absence of unified I-d-diagrams suitable for pressure. The essence of the developed technique is to determine the curves on the atmospheric I-d-diagrams, graphically coinciding with the curves A numerical example of the application of such a technique is given. The advantages and disadvantages of both methods are evaluated.

An Efficient Quantification Method Based on Feature Selection for High-Dimensional Uncertainties of Multistage Compressors

Abstract Multistage compressors are widely used in aero-engines, gas turbines, and industrial compressors. However, many inevitable geometric/condition uncertainties will lead to low manufacturing qualified rate and severe performance degradation of multistage compressors. There might be hundreds of uncertainty variables simultaneously, so the “curse of dimensionality” problem has seriously constrained the uncertainty quantification (UQ) study in multistage compressors. In this paper, a feature selection method based on interpretable machine learning and bidirectional search is developed to reduce the dimensionality in a multistage compressor UQ study. The method is applied to a three-stage compressor and reduces the uncertainties dimensionality from 292 to 41 and 66 for mass flow rate and efficiency prediction. Consequently, the required sample size is reduced from 1674 to 160 with the model accuracy almost unchanged. For the first time, this study realizes the UQ modeling study on the high dimensional problem of a multistage compressor. In addition, significant stage-by-stage uncertainty propagation is found in the compressor. The last stage has the most significant efficiency deviation, which is significantly affected by the geometric uncertainty of the first two stages. Therefore, traditional studies, which usually simplify the multistage compressor UQ problem to a single cascade/row level, may seriously underestimate the uncertainty effect due to the neglect of stage-by-stage propagation. This study not only reveals the necessity for direct UQ study of multistage compressors but also reduces the computational cost, which lays a foundation for the uncertainty control of multistage compressors in engineering practice.

Casing Treatment: Its Potential and Limitations

Abstract Casing treatment is an advanced design feature intended to improve the stability of a compressor. Various investigations have been conducted based on both experimental and numerical studies at least over the last 50 years. In general, it has been demonstrated that a careful design of a casing treatment can substantially improve the stall margin of a tip-limited compressor although this generally comes with an aerodynamic efficiency penalty. This review paper revisits important past studies on casing treatments to clarify findings on the sometimes-conflicting results and understand what lessons are generally applicable to a wider group of machines. Circumferential grooves over a rotor tip have been in use for some time. Much recent work has focused on axial slots over a rotor tip, because of the significant stall margin improvement and the better efficiency potential of this configuration. This paper includes both configurations, with more emphasis on the latter. The paper concludes that casing treatment offers powerful benefits to a compressor and deserves continuing research and development. Good benefits result from axial slots which start ahead of the rotor leading edge and cover the front part of the rotor tip and include skew (tangential lean in the direction of rotation). Contributing physical mechanisms include increasing the axial momentum of the casing flow casing and reducing the aerodynamic blockage to improve the casing boundary layer and the tip leakage flow. The role of impacting unsteadiness is yet to be further clarified. Areas of further research are recommended, both experimental and analytical, including further work to understand and control the loss mechanisms, studying and controlling stage interaction effects in multistage compressors, and the simultaneous design optimization of the rotor blade with the casing treatment. Multi-disciplinary issues such as manufacturing cost, weight, length, durability, aeromechanics effects, and tolerance to dust and ice also deserve further attention.

Metamodel-Interpreted Data Mining for Stability and Efficiency Enhancement of Multistage Axial-Flow Compressors

Abstract The tradeoff between higher efficiency and wider stability of performance map is still one of the bottlenecks to hamper the further research and development of advanced multistage axial-flow compressor. The recent rapid growth of computational resources and artificial intelligence has enabled data mining as one of the most effective and potential ways to gain a deep insight into the complex correlations between aerodynamic performance and three-dimensional geometry parameters. In the open literatures, however, few research works have been found on using the data mining that is independent of design optimization to extract priori design guidelines for multistage axial-flow compressor mainly due to the lack of proper data mining method focused on the interpretation of metamodel with full use of limited time-consuming computational fluid dynamics dataset. To tackle this issue, a metamodel-interpreted data mining framework is developed in which extreme gradient boosting (XGBoost) metamodel combined with Shapley additive explanation (SHAP) model are employed to locally interpret the feature importance of each sample in the computational fluid dynamics dataset and then extract the design guidelines in terms of the most influential geometry parameters and their beneficial variation directions. The developed method is applied to data mining of design guidelines for efficiency and stability enhancement of a front 3.5-stage transonic axial-flow compressor in ship-board gas turbine usage. The results show that the aerodynamic performance of the investigated multistage compressor is most sensitive to three-dimensional geometry parameters related to blade lean, blade twist, and variable stators. Specially, the variable stators mainly affect the stall margin at part speed. The blade lean mainly influences the adiabatic efficiency at design speed as well as the stall margin at both speeds, while the blade twist mainly influences the aerodynamic performance at design speed. New designs followed by the design guidelines are obtained and critical performance indicators related to the goals of the data mining task are verified. The stall margin at part speed is widened to 5.87% with adjustment of blade lean and twist and further to 23.31% with additional adjustment of variable stators. The peak adiabatic efficiency at design speed is improved by 0.06% in spite of extremely limited potential for efficiency enhancement of the original design. The present work is of scientific significance as well as industrial application value in the three-dimensional design optimization of advanced multistage axial-flow compressor at the affordable computational cost.

Evolution of Turbulence and Its Modification by Axial Casing Grooves in a Multi-Stage Axial Compressor

Abstract This experimental study examines the evolution of turbulence across an axial compressor and its modification by semicircular axial casing grooves (ACGs) at the pre-stall and near the best efficiency (BEP) flowrates. The turbulence is highly anisotropic and spatially inhomogeneous, with each normal Reynolds stress component evolving differently. Most of the observed trends can be explained by examining the dominant production rate terms. At the pre-stall flowrate, the turbulence increases significantly upon entering the rotor with peak RMS values of axial velocity fluctuations reaching as high as 71% of the mean axial velocity. The region with elevated turbulent kinetic energy (TKE) covers 30% of the outer span near the rotor leading edge, expanding to 50% near the trailing edge. While the TKE in the outer span decays rapidly in the stator, the local turbulence production persists in the stator blade boundary layer. By stabilizing and homogenizing the flow, the ACGs reduce the turbulence production, hence the TKE, in the rotor and the stator. The only exception is an increase in turbulence in the region dominated by groove–passage flow interactions. Near BEP, the TKE is much lower everywhere, except for the region influenced by the outflow from grooves. Downstream of the rotor and the stator, the turbulence level with or without ACGs are similar. The large variations in the magnitude and even the sign of the measured eddy viscosity highlight the extreme non-equilibrium conditions over the entire machine, questioning the fundamental assumptions of local equilibrium in eddy viscosity-based Reynolds stress models.

Numerical analysis of a miniature multi-stage compressor at variable altitudes based on stages-in-series method

Oil-free miniature multi-stage compressor (MMSC) is significant for delivering clean compressed air to mobile applications, and its thermodynamic performance can be greatly influenced by environmental factors. In this research, a stages-in-series numerical model for the multi-stage swash-plate compressor was established by comprehensively considering the real-time variations of gas properties in the intercooler flow channels. On this basis, the thermodynamic performance of the compressor at variable altitudes with different environmental characteristics was studied numerically. The results showed that the volume flow rate of the compressor decreases nonlinearly as the altitude increases. With each 2000 m increase in altitude, the total indicated power required by the compressor reduces by approximately 19 %. The volumetric efficiency of the first, second and third stage cylinder decreased by 0.86 %, 4.01 %, and 9.41 % on average, respectively, which means that the 3rd stage cylinder is the least suitable for high altitudes.

Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence

Abstract The paper describes the study performed by SoftInWay in the scope of the Phase I SBIR project funded by the National Aeronautics and Space Administration (NASA). The project was dedicated to a study of optimization of the variable geometry reset angle schedules with the use of innovative autonomous artificial intelligence (AI) technology. In the scope of the project, an automated compressor performance data generation workflow was developed. Three highly loaded multistage axial compressors were designed. The developed workflow was used to generate the training, validation, and test data sets for all three compressors. Multiple different architectures of artificial neural networks were studied, and parametric models for the representation of performance speedlines were developed. Utilizing the developed approaches, artificial neural networks were trained for all three compressors to predict their performance with a relative error below 3%. The trained neural networks were successfully used in the optimization of the variable inlet guide vanes and variable stator vanes reset angle schedules with a relative error of total-to-total pressure ratio prediction below 2% for most of the points and relative error of total-to-total efficiency prediction below 1% for all the points of the operational line. The capability of the developed AI models to accurately predict the optimal combination of reset angles and efficiency of the axial compressor with multiple vanes controlled independently allowed doing quick evaluations of efficiency and stability margins. The availability of such information enables the opportunity to make technical-economical decisions about the reasonability of implementation of independent variable vanes and their number during engine system analysis.

A mathematical model for refinery hydrogen network synthesis integrating multi-stage compressors

The synthesis of refinery hydrogen network (HN) is generally performed under the assumption that compressors are single-stage ones. This assumption might overestimate the compression power, leading to deviation from the optimum designs. To tackle this problem, we integrate multi-stage compressors into hydrogen networks synthesis in the present work. The number of compression stages inside each compressor is defined as a variable which is simultaneously optimized with the network configurations. Taking advantage of the discrete nature of the defined stage variable, we linearize the constraint of compression power without losing generality. The proposed mathematical model for HN synthesis is formulated as a mixed-integer nonlinear programming problem. Three instances are conducted and the solution results show that the proposed model could be solved to global optimality. The total annualized costs of globally optimal solutions are 1.4–5.1% lower than those of the base solutions.

Basic Nature of Behaviors of Surge Frequencies in Multi-Stage Axial Flow Compressors

The behaviors of surge frequencies in multi-stage axial-flow compressors are studied by use of several non-dimensional parameters on the basis of numerical-experimental results. One of the essential parameters proves to be a flowpath-average reduced surge frequency multiplied by the stalling pressure ratio and the tip-Mach number. Framework map in terms of such parameters against reduced resonance frequencies can provide a whole view of the surge frequency behaviors, including various characteristic zones of surge behaviors, i.e., convective surges, near-resonant surges, degenerated surges, and multi-stage effects. Particularly, for the convective surges, the surge frequency parameter comes to have a nearly constant value over a wide range of the reduced resonance frequencies, independently of number of stages, speeds, and pressure ratios, etc., of the compressors. The map is practically useful for the evaluation of deep-surge frequencies. At the same time, it could form a base for further investigations into the surge phenomena.

Investigation on the thermodynamic performance of a small multi-stage swash-plate compressor under different ambient temperature

Small multi-stage swash-plate compressors are key components in many industrial equipment for supplying clean compressed air. When operated on earth, their thermodynamic properties can be significantly affected by extreme ambient temperature. This paper proposes stages-in-series mathematical models to simulate the real operating state of a small multi-stage swash-plate compressor. The coupled interaction between inter-stage gas channels and each stage cylinder are considered in the model. The real-time variation of in-cylinder and in-intercooler thermodynamic properties such as pressure, temperature, mass flow and volumetric efficiency with ambient temperature are predicted. The results show that ambient temperature exists significant influence on the thermodynamic properties of the intercooler and cylinders. The volume flow rate decreases from 12.28 SL/min to 11.28 SL/min when ambient temperature increases from 233.15 K to 253.15 K and when ambient temperature rises to 333.15 K, the flow rate decreases to 8.49 SL/min. Additionally, it is found that ambient temperature exerts more significant influence on volume flow rate compared to indicated work. This study can provide valuable reference for operation of multi-stage swash-plate compressors and other multi-stage reciprocating compressors under extreme ambient temperature.

Reduced Order Modeling of Forced Response in a Multistage Compressor Under Mistuning and Aerocoupling

Abstract Vibration amplitudes and fatigue life in multistage turbomachinery are commonly estimated by an investigation of the individual stages. Research is currently extending the scope to include structural and aeroelastic interstage coupling. Both effects have been shown to significantly influence blade vibrations. For safe operation of modern blisk blading with its lower structural damping due to the elimination of frictional contacts at the blade roots, an accurate prediction of the vibration behavior with mistuning is necessary to avoid high cycle fatigue failures. In this paper, a cyclic Craig-Bampton reduction method with a priori interface reduction for multistage rotors is extended to handle aeroelastic effects. This reduced order model efficiently predicts forced response in multistage applications. Aeroelastic multistage simulations are carried out using the harmonic balance method to account for the stage interactions and yield damping and stiffness coefficients, as well as excitation forces. Small structural mistuning is projected onto the tuned system modes of the rotor. The approach is applied to a 2.5-stage compressor configuration. Monte Carlo simulations show the sensitivity of vibration amplitudes to the aeroelastic coupling for mistuning. The aeroelastic interstage coupling is found to originate mainly from acoustic mode propagation between the stages. The fatigue of rotor blades is significantly affected by multistage interactions since vibration amplitudes increase due to the superposition of the responses of multiple modes. This leads to the conclusion that aeroelastic multistage effects need to be incorporated in future design procedures to allow for an accurate prediction of fatigue life.

Performance dispersion control of a multistage compressor based on precise identification of critical features

Multistage compressors are widely used in essential equipment such as aero-engines, gas turbines, and industrial compressors. However, there are hundreds of geometric deviations with uncertain characteristics in the manufacture and maintenance of multistage compressors, resulting in severe performance dispersion. If the geometric deviation is strictly controlled, the performance dispersion can be effectively controlled, but the manufacturing and maintenance costs are high; otherwise, the costs can be reduced, but the performance dispersion is large. To solve the above contradictions and realize the synergistic optimization of the performance and cost of multistage compressor manufacture and maintenance, it is necessary to accurately identify critical geometric features affecting the performance dispersion from the numerous features. Then only the critical features are strictly controlled rather than all features. In this paper, combining the neural network and interpretable machine learning methods, a feature selection method based on the bidirectional search is developed to achieve fast and accurate identification of critical geometric features in multistage compressors. This method is applied to a 3-stage compressor. Fifteen critical features are accurately identified from the original 291 geometric uncertainty features to control the mass flow rate dispersion. When reducing the deviation ranges of the 15 features to half, the mass flow rate dispersion can be reduced by 48%, while reducing the deviation ranges of the other 276 features to half, the dispersion can only be reduced by 5%. For efficiency dispersion control, 60 critical geometric features are accurately identified from the original 291 geometric uncertainty features. When reducing the deviation ranges of the 60 features to half, the efficiency dispersion can be reduced by 35%, while reducing the deviation ranges of the other 231 features to half, the dispersion can only be reduced by 14%. This paper proposed a performance dispersion control method for multistage compressors based on the accurate identification of critical features. This method can provide an effective solution for the performance dispersion control in multistage compressor manufacture and maintenance, which lays the foundation for the collaborative optimization of compressor performance and cost.

Multidimensional resilience decision-making for complex and substructured systems

Complex systems, such as infrastructure networks, industrial plants and jet engines, are of paramount importance to modern societies. However, these systems are subject to a variety of different threats. Novel research focuses not only on monitoring and improving the robustness and reliability of systems, but also on their recoverability from adverse events. The concept of resilience encompasses precisely these aspects. However, efficient resilience analysis for the modern systems of our societies is becoming more and more challenging. Due to their increasing complexity, system components frequently exhibit significant complexity of their own, requiring them to be modeled as systems, i.e., subsystems. Therefore, efficient resilience analysis approaches are needed to address this emerging challenge.This work presents an efficient resilience decision-making procedure for complex and substructured systems. A novel methodology is derived by bringing together two methods from the fields of reliability analysis and modern resilience assessment. A resilience decision-making framework and the concept of survival signature are extended and merged, providing an efficient approach for quantifying the resilience of complex, large and substructured systems subject to monetary restrictions. The new approach combines both of the advantageous characteristics of its two original components: A direct comparison between various resilience-enhancing options from a multidimensional search space, leading to an optimal trade-off with respect to the system resilience and a significant reduction of the computational effort due to the separation property of the survival signature, once a subsystem structure has been computed, any possible characterization of the probabilistic part can be validated with no need to recompute the structure.The developed methods are applied to the functional model of a multistage high-speed axial compressor and two substructured systems of increasing complexity, providing accurate results and demonstrating efficiency and general applicability.

Методика и опыт первичного проектирования трансзвукового осевого компрессора

The article considers the basic principles underlying the program for the calculation and designing gas turbine engine axial compressors. Calculation of pressure losses and deflection ability of the cascades is based on the formulas of A. Komarov. The model involves empirical coefficients, the values of which were selected during program verification based on the results of testing multistage compressors and compressor stages. The basic equations and the algorithm for calculating pressures and velocities are given under the condition of radial balance. The application of computer programs based on these models in designing a gas turbine engine four-stage compressor of moderate power with a total pressure ratio of 3.2 and a given speed is shown. For the first compressor stage, two options with different flow rates are compared. The first option was designed according to the classic recommendation to get close to the same mechanical energy of the gas at the exit of the stage along the radius. The second option was designed for a lower flow coefficient, but ensuring the radial balance, requires introducing a significant non-uniformity of mechanical energy supply along the radius. Due to the lower kinetic energy, the stage efficiency of the second variant is 1.9 % higher, despite the fact that the loss coefficients of the blade cascades are lower in the first variant. The question remains as to how much the inevitable mixing losses in the second variant will reduce its efficiency in the process of equalizing the mechanical energy of the gas

Effect and Mechanism of Roughness on the Performance of a Five-Stage Axial Flow Compressor

In order to prolong the service life of multistage axial compressors, it is increasingly important to study the influence of blade surface roughness on the compressor performance. In this paper, a five-stage axial compressor of a real aero-engine was selected as the research object, and an equivalent gravel roughness model was used to model the roughness based on measured blade surface roughness data. Furthermore, the impact of blade surface roughness on the performance at design rotational speed was studied by full three-dimensional numerical simulation, and the mechanism of performance variation caused by the roughness was discussed combined with quantitative and flow field analyses. The results show that, when the blade surface roughness of all blades increases, the peak total efficiency decreases by approximately 0.4%, the blocking mass-flow decreases by approximately 0.3%, and the stable working range changes little. When the surface roughness of all rotor blades increases, the performance decline is close to that of all rotor and stator blades, and the variation in stator blade roughness has little effect on the compressor performance. Regarding the variation in roughness, the performance of the latter stage is more sensitive than that of the previous stage, and the decline in the performance of the fifth stage contributes the most to the total performance degradation of the compressor. Once the surface roughness of the fifth-stage rotor blade increases, the flow in the middle of the rotor blade deteriorates and the stage performance decreases obviously, which is the main reason for the decline in the overall performance.

A Computational Method of Rotating Stall and Surge Transients in Axial Compressor

The onset of rotating stall and surge in compressors limits the operating range of aero-engines. Accurately predicting the key features during these events is critical in the engine design process. In this paper, a three-dimensional computational model for transient simulation of multi-stage axial compressors during stall is proposed. The kinetic equations describing the dynamic process of the compression system are constructed, with a 3D through-flow model for the compression part and a 1D gas collector model for the outlet part. The calculation of the source term is performed using the developed body-force model, which realizes the correlation between the deviation angle and the loss coefficient with the inlet parameters in various flow regions. Validated on a single-stage compressor and a single-rotor fan, the results show that the method is capable of capturing the stall and surge features correctly and that the three-dimensional structure of the stall cell can be captured. In addition, this model could be used for the analysis of the surge load, which is significant for the structural integrity of the compressor.