Compressor Design Research Articles

Centrifugal compressor design and cycle analysis of large-scale high temperature heat pumps using hydrocarbons

Using natural refrigerants in heat pumps, including hydrocarbons, is becoming attractive because of the tightening regulations concerning synthetic refrigerants. In the literature there is lack of studies investigating detailed component design, including compressor design when using hydrocarbons. This study investigates numerically centrifugal compressor design with hydrocarbons for large-scale high-temperature heat pumps. The compressor analysis was combined with a thermodynamic analysis of a two-stage heat pump. The effect of temperature lift and flash intercooler temperature on compressor sizing, rotational speed, efficiency, axial force, and Mach number were investigated. Generally, the use of hydrocarbons with five carbon atoms resulted in higher coefficient of performance and required lower compressor rotational speeds and larger compressor dimensions when compared to the hydrocarbons with four carbon atoms. The simulated rotational speeds were ranging from 8 krpm to 30 krpm, impeller diameters from 0.15 m to over 0.7 m and compressor efficiencies from 77% to over 85%. The use of cyclic molecules, namely cyclopentane and cyclobutene resulted in the highest heat pump coefficient of performance. Also, the flash intercooler temperature had a notable effect on the compressor design and axial force which has to be taken into account in heat pump cycle design.

Performance prediction and Bayesian optimization of screw compressors using Gaussian Process Regression

Optimizing the performance of screw compressors is critical for achieving high efficiency and reducing costs in various industrial and engineering applications. Often, the design and optimization processes are time-consuming owing to the underlying iterative complex analyses. In this context, the present research investigates the potential of Gaussian Process Regression (GPR) and Bayesian optimization for the prediction and optimization of the performance of an oil-flooded screw compressor. Specifically, the GPR-based surrogate model is developed to predict the compressor performance characteristics based on its four main geometrical design parameters such as wrap angle, relative length, tip speed of the male rotor and built-in volume ratio. The model is trained using a dataset comprising 19,200 data points relating the input design parameters with the compressor performance, obtained using physics-based multi-chamber thermodynamic models. While four different learning algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Polynomial regression and GPR are explored, the GPR performed the best resulting in an R2 value of 0.99 for the test dataset after hyperparameter tuning. Further, the model is also experimentally validated on a completely unseen dataset, showing very good predictions with a maximum error of 5%. The resulting surrogate model is then used to optimize the compressor design parameters using Bayesian optimization. The results are compared with optimization using Genetic Algorithm (GA) and physics-based multi-chamber thermodynamic model. It was shown the proposed approach results in similar optimal design parameters but with a significantly less optimization time by a factor of 7. The study highlight the potential of machine learning-based prediction and optimization of screw compressors in engineering applications.

Flow physics during durge of an axial-centrifugal compressor

Aerodynamic instability design is one of the crucial elements when designing a compressor. Unstable phenomenon such as surge harms the compressor in both performance and structure integrity. The complex unsteady flow process during instability strongly relates to the compressor design. This paper investigates the transient instability process using URANS on a three-stage-axial and one-stage-centrifugal combined compressor under its off-design conditions. Results show that the compressor suffers two surge patterns. The mild surge happens first, with a higher frequency than the traditional mild surge. Then, with the decrease of valve opening, the deep surge is initiated, and the axial stages work at the peak pressure ratio because the mass flow rate is limited by the choked radial diffuser. Moreover, analysis of aerodynamic loads reveals that IGV and the first rotor have the largest unsteady force among all blade rows. According to the flow field, the rotor root and stator tip suffer the most serious impulse caused by reversed flow during surge conditions.

Experimental Investigation on the Aerodynamic Instability Process of a High-Speed Axial-Centrifugal Compressor

Abstract Aerodynamic instability plays an important role in compressor design and may cause performance degradation and fatigue damage. In this paper, an experimental study on the evolution of aerodynamic instability is carried out on a compressor that combines the performance benefits of an axial stage and centrifugal stage. The spatiotemporal characteristics of unsteady wall pressure were obtained using fast-responding pressure transducers over a range of operating conditions. The results show that the axial stage works on the positive slope of the performance characteristic curve from choke to stall at low-speed operating conditions, and mainly features rotating instability. Rotating stall is also observed in the impeller (IMP) and diffuser passages. At medium-speed operating conditions, the centrifugal stage suffers a high-frequency mild surge, alternating with rotating stall. With the increase in back pressure, the mild surge diminishes, and rotating stall persists. This behavior is similar to a two-regime-surge, which has been reported for centrifugal compressors. At high-speed operating conditions, the compressor directly reaches surge without other instabilities. Further analysis of the spatial pattern of the rotating stall revealed the existence of a high-pressure region near the volute tongue, resulting in obvious pressure distortion along the circumferential direction at the volute inlet. This induced the amplitude difference of stall cells in corresponding diffuser passages. The disturbance caused by stall cells propagates upstream through the blade passage, and the largest pressure disturbance induced by the stall cell propagation appears in a circumferential position 45 deg downstream of the volute tongue at the impeller inlet and the axial stage inlet.

Optimization and experimental study of stationary endwall of stator labyrinth cavity in a low-speed research compressor

Controlling the leakage flow of the labyrinth seal cavity is very important for the efficiency and aerodynamic matching design of aero-engine high-pressure compressor. However, due to the complexity of the geometry and internal flow of the labyrinth seal cavity, the design optimization of the labyrinth seal cavity is rarely studied. In this paper, a multi-objective design optimization method was used to optimize the stationary endwall of the shrouded stator labyrinth cavity, and the optimal endwall shape was obtained. Based on the optimal geometry, the 3D printing and aerodynamic testing of experimental parts were carried out, and the aerodynamic performance and flow field details of the optimal geometry were analyzed by unsteady numerical simulation. The experimental results show that for the optimal geometry, it has a little effect on the total pressure ratio, but the efficiency at the design point is increased by 1.4 %. The numerical results show that the optimal cavity shape reduces low-energy fluid, thus reduces the total pressure loss of S3. At the near stall point, the optimal S3 still has a better performance, which means that the optimal shape is not limited to the design point. From the result, an engineering design criterion can be concluded. It is suggested that the labyrinth seal cavity should be designed to match the velocity components of the leakage flow with the mainstream of the stator properly to make the leakage flow go evenly in the blade passage instead of gathering to the suction side.

Research on thermal deformation and clearances of oil-free twin screw compressor under cryogenic conditions

The oil-free twin screw compressors have obtained increasing attention in the field of boil off gas (BOG) recovery since they effectively reduce the power consumption and have higher reliability when recovering and boosting BOG. However, the thermal deformation of compressor under cryogenic operating conditions will lead to the change of clearance. The unidirectional thermal-fluid-solid coupling method is proposed in this paper to solve the problem and analyze the thermal deformation of compressor and the changes of each clearance caused by the deformation at different meshing angles in a meshing cycle. It is shown in the results that the deformation of twin screw compressor at low temperatures is a kind of cold shrinkage deformation. The combined effect of the deformation of various components has a significant influence on each clearance. Furthermore, it is reasonable to set the tooth tip clearance of the male rotor, suction end clearance and meshing gap as 0.3 mm, 1 mm and 0.3 mm respectively, which do not cause dangerous working conditions. Inappropriate clearance values lead to friction between parts in the local area. The simulated result of the dangerous friction area in twin screw compressor shows good agreement with the friction area in the compressor test. According to the simulation and test results, the tooth tip clearance of the female rotor is modified to 0.35 mm, and the discharge end clearance is adjusted to 0.1 mm. The results show that the modified compressor can working reliably. This study provides guidance for the design and processing of oil-free twin screw compressors employed in the situation of BOG recovery.

Design and analysis of centrifugal compressor in carbon dioxide heat pump system

Based on the advantages of energy saving, environmental protection and high efficiency, carbon dioxide heat pump system has great application prospects. However, there are still many technical problems to be solved, especially the design and optimization of carbon dioxide centrifugal compressor. In this paper, a centrifugal compressor in carbon dioxide heat pump system is designed. The compressor is directly driven by a high-speed permanent magnet synchronous motor. Two-stage impellers are installed on both sides of the motor, and the bearings are active magnetic bearings. The influences of inlet pressure and temperature on compressor performance are analyzed. In the range of inlet temperature from 35 to 55 °C, with the decrease of inlet temperature, the compressor pressure ratio increases by 12–29.8%, the power increases by 2.7–8.6%. In the range of inlet pressure from 4 to 6 MPa, with the increase of inlet pressure, the compressor pressure ratio increases by 12.3–38.6%, and the power increases by 8.7–17.8%. In addition, the calculation method of compressor axial force is introduced, the axial force is calculated, analyzed and optimized. Furthermore, the rotor dynamics of compressor rotor and the influences of bearing stiffness and diameter of motor rotor on rotor dynamics are studied. With the increase of bearing stiffness, the first-order critical speed and maximum displacement of the rotor increase. The research provides a theoretical reference for the design and optimization of centrifugal compressor in carbon dioxide heat pump system.

Prediction of performance parameters of a hermetic reciprocating compressor applying an artificial neural network

The efficiency of the compressor's thermodynamic, mechanical, and electric motors can be increased by minimizing their losses. Based on the design characteristics of the compressor, the current study proposes an artificial neural network (ANN) model to forecast the mass flow rate, cooling capacity, compression power, and discharge line loss of the hermetic reciprocating compressor as outputs. This study uses experimental and numerical results obtained by the fluid–structure interaction (FSI) method, and the whole findings are used as inputs for the machine learning method. Using 36 numerical and 3 experimental data sets, a multilayer network is created with input parameters defining mass flow rate, cooling capacity, compression power, and discharge line energy loss. The input parameters for the network model are the compressor's design parameters, which include the compressor speed, discharge valve thickness, and discharge valve length. When comparing the experimental and FSI methods for compressor speeds of 1300, 2100, and 3000 rpm, the FSI study's mass flow rate and cooling capacity parameters converged at 11.9%, 9.1%, and 9.3%, respectively, to their actual values. The convergence rate to experimental compression power data was −0.3%, 2.6%, and 11%. The numerical-experimental deviation for discharge line energy losses is 14.9%, −3.6%, and 7.8%, respectively, for 1300, 2100, and 3000 rpm. With the Levenberg–Marquardt (LM) ANN model, which is used in this study, the average squared error value is calculated as 1.75E-02 and the R2 value is calculated as 0.99976. ANN model can predict outputs with average deviation rates of less than 0.88%. It is seen that results obtained with the ANN method provide high convergence on the experimental and FSI results, while the results obtained with the regression model deviate from the compressor exhaust line results by more than ±20%, and the ANN method is more successful than regression.

Thermo-fluid dynamic modeling of a supercritical carbon dioxide compressor for waste heat recovery applications

The development of novel technical solutions for the efficient recovery of waste heat is crucial for making accessible the large amount of thermal energy released by industrial processes, thus supporting the EU energy strategy. To this end, the EU-H2020 project CO2OLHEAT aims at developing and demonstrating a novel sCO2 power unit of 2 MW capacity, recovering energy from flue gases at 400 °C. The CO2OLHEAT system features a relatively unconventional multi-shaft configuration where the sCO2 compressor is driven by a dedicated radial expander, while the electrical power is generated via a separated axial turbine.The present study focuses on the design and fluid-dynamic analysis of the CO2OLHEAT compressor. The thermodynamic optimization of the cycle led to an overall pressure ratio slightly above 2.5, delivered with a two-stage centrifugal compressor. As typically found in sCO2 power systems, the thermodynamic state of the fluid at the machine intake (P = 85 bar; T = 32 °C) is close to the critical point and to the saturation curve; therefore, the first stage of the machine demands a dedicated aero-thermodynamic design, which can account for the effects of non-ideal thermodynamics and of the potential onset of two-phase flows. The paper discusses the conceptual aero-mechanical design of the compressor and then focuses on its performance assessment over the full operating range via Computational Fluid Dynamics. Two alternative CFD models are applied, the first one based on the barotropic fluid representation and the second one featuring a complete thermodynamic model, both of them assuming homogeneous equilibrium in presence of multi-phase flows. The experimental validation and the application of the two models are presented and discussed. They are shown to provide similar outcomes, and indicate that the compressor fulfills the system requirement and guarantees wide rangeability. A thorough comparison between the CFD results highlights the implications of the underlying physical differences between the models, thus allowing to properly evaluate their use for the aerodynamic design and analysis of sCO2 compressors.

The effect of a tandem vane crossover diffuser configuration on the performance of a MGT mixed flow compressor

Due to the inherent geometric restrictions of a micro gas turbine (MGT) mixed flow compressor design, diffuser design has a major impact on compressor performance and operating range. Vaned diffusers are often preferred to vaneless diffusers in MGT compressor designs due to better efficiency and pressure recovery, albeit at the expense of operating range. A numeric investigation of the effect of a tandem vane crossover diffuser configuration on the performance and operating range of a MGT mixed flow compressor stage is presented. Three baseline test compressors, covering a wide range of design speeds, mass flow rates and meridional exit angles, are designed with a single vane crossover diffuser. For each of the three baseline compressors, the crossover diffuser design is modified to feature various tandem vane configurations. The tangential shift of the second vane row relative to the first row is evaluated. Additionally, relative first and second vane row lengths are evaluated. The performance (efficiency and pressure ratio) and operating range of the modified diffuser configurations are compared to the baseline configurations. It is shown that a 75% second vane row tangential shift configuration displays the best overall performance, regardless of the relative vane length. It is further shown that an appropriate vane length depends on the design requirement.

Updating Turbomachinery Aerodynamics Teaching on an Undergraduate Course Using Three-Dimensional Design Tools

Abstract This paper outlines the update of a turbomachinery course to cover three-dimensional (3D) aerodynamics using a Reynolds-Averaged Navier Stokes solver. Prior to the activities outlined in this paper, the course was taught in a conventional way with a series of lectures and a timed, written, open book examination in a formal exam setting. Students were equipped with a calculator and set of notes including correlations from Howell and Soderberg. The students had around 1 h to answer the turbomachinery question, which was revealed to them only when they opened the paper at the start of the exam. This limited the depth of any aerodynamic problem they could get through and so they were restricted to simple design or analysis exercises. The genesis of the course update was the release in 2017 of “MULTALL OPEN” (Denton, J. D., 2017, “Multall: An Open Source, Computational Fluid Dynamics Based, Turbomachinery Design System,” ASME J. Turbomach., 139(12), p. 121001), a freely available turbomachinery design system, and this was adopted as the course software—although other software choices were considered. Students now produce two turbomachinery designs during the course. These are both based on the J85 turbojet—largely to keep cycle calculations to a minimum but it was also important to ensure that students recognize that they were completing a real engineering task. The first task was a 3D aerodynamic design of multistage turbine, which includes compressible flow, tip clearance, and stacking techniques such as lean or sweep. The second task was a midspan (two-dimensional) compressor design. The exact cycle conditions were varied each year to explore design scenarios such as an increase in firing temperature. Assessment was by means of a short report where the best students report on their design choices, provide critical analysis of the design using appropriate postprocessing techniques, and compare their designs to the state of the art in the wider literature. As well as describing the successes and challenges of the update to 3D design methods the paper provides some guidance for educators thinking about adopting a similar approach.

An axisymmetric characteristic model for enhancing prediction of centrifugal compressor characteristics

Rapid and accurate determination of compressor characteristic maps is essential for the initial design of centrifugal compressors in aircraft power systems. The accuracy of existing methodologies, which rely on combinations of loss models, varies significantly depending on the compressor’s geometry and operational range. This variance necessitates substantial experimental or Computational Fluid Dynamics (CFD) data for coefficient calibration. To address this challenge, this study presents an axisymmetric characteristic model for compressor performance assessment. This model incorporates the factors of blade angle, meridional passage area, and the radial deflection angle of meridional streamlines of the compressor. These factors are derived from fundamental aerodynamic equations encompassing mass, momentum, and energy conservation of the compressor. In contrast to conventional one-dimensional approaches, the proposed method reduces the number of loss coefficients and more effectively accounts for the impact of geometric alterations on centrifugal compressor properties. Furthermore, the model reduces dependence on experimental and CFD data. Efficacy of the model is validated using experimental data from four distinct types of centrifugal compressors. Correlation analysis reveals that the model’s coefficients can be expressed as functions of the ratio of the Reynolds number to the impeller tip speed. This ratio serves as a characteristic parameter for the design and optimization of centrifugal compressors. Consequently, the proposed method offers an efficient and accurate means for the quick computation of centrifugal compressor characteristics. This is of great significance for improving the efficiency of centrifugal compressors and reducing energy consumption.

Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence. Phase 2

Abstract This paper discusses a study performed by SoftInWay as part of a Phase II SBIR project funded by NASA. In contrast with the Phase I project (Burlaka and Moroz, 2023, “Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence,” ASME J. Eng. Gas Turbines Power, 145(1), p. 011001) where three discrete compressors were considered, the Phase II study was focused on addressing the problem of axial compressor long development time and cost with the use of AI models capable of predicting the geometry and performance of various multistage axial compressors with multiple variable vanes. The applicability of the AI models to various compressors enables the opportunity to avoid iterations between engine cycle analysis and compressor design. In this paper, automated compressor design and performance generation workflows are described. The approach for autonomous selection of the architectures and hyperparameters of Machine Learning (ML) models is explained. The uncertainty quantification techniques are considered. The developed ML-powered methods for compressor geometry prediction are discussed. The ML models' accuracy values and representations of typical geometry and performance predictions are given. The utilization of the ML models in engine cycle analysis is discussed.

Design and numerical simulation analysis of a miniature Mixed-flow compressor

This paper completed the pneumatic design of a mixed-flow compressor, adopted RANS turbulence model, and chose Spalart-Allmaras model to complete the numerical simulation of the flow field of the S1 flow surface, meridian flow surface, and impeller surface, and then analyzed the working performance at 90%, 100%, and 110% design speed to explore whether the mixed-flow compressor technology suitable for micro turbojet engines as well as the internal flow field flow state and loss mechanism. The results indicate that the shock wave at the front edge of the main blade and the low energy gas gathered at the tail edge of the main blade and the shunt blade, which causes serious flow blockage, are the main causes of the instability of the mixed-flow compressor at the design point. At 100% design speed, the compressor has higher reliability, stronger adaptability, and the best working performance for its working margin, isentropic efficiency, and pressure ratio with lower loss. The results may provide some references for the further optimization design of the current compressor.

A review of compressor design for future aircraft propulsion architectures

A review of compressor design for future aircraft propulsion architectures

Data-driven compressor performance maps and cost correlations for small-scale heat-pumping applications

The performance of vapour-compression heat pumps depends crucially upon compressor selection and design. In this work, a unified modelling framework is developed to enable technoeconomic comparisons of compressors intended for small-scale heating applications (<30 kWth). Published information on 120 commercially available compressors is analysed and used to develop performance maps that predict isentropic efficiency over a wide range of working conditions. Additionally, cost correlations are established to predict price as a function of nominal compressor inlet volumetric flowrate. When rotary-vane compressors are an available option (i.e., for inlet volumetric flowrates up to 5 ∙ 10−3 m3/s), they consistently achieve a high isentropic efficiency (∼70 %) for the investigated pressure ratios (1.5–9.5). Scroll compressors have an even higher isentropic efficiency (∼75 %) at pressure ratios below 5.5, but this drops to 50 % at higher pressure ratios, while the isentropic efficiency of reciprocating-piston compressors is best (∼75 %) at higher pressure ratios (5.5–7.5). Utilising an air-source heat pump model, the compressor types are compared for countries with different weather characteristics and electricity prices. Rotary-vane compressors are associated with the lowest levelised cost of heat, but the comparison largely depends on location and heating requirements.

4:2 Compressor Design for Low Leakage Applications in FinFET Technology

The increased short-channel effects in the ultra-nanoscale regime limit the operation of complementary metal oxide semiconductor (CMOS) technology. To combat the issues in the ultra-nanoscale regime, fin-shaped field effect transistor (FinFET) technology is the best choice because of its numerous advantages over CMOS technology. FinFET enhances the further scaling of the devices and control over the channel. Therefore, this research paper presents the implementation of a low leakage 4:2 compressor in FinFET technology. A compressor is a general block, especially used in multiplier units and hence in digital signal processing (DSP) systems. The design of the low power compressor improves the overall efficiency of the DSP systems. An extensive study of the proposed low power 4:2 compressor at 7 nm technology node is done in the paper. Mentor Graphics tools are used for the circuit simulations and analyzes. The key parameters, such as leakage power, delay, power delay product (PDP), and the process voltage temperature (PVT) variations, are estimated for the performance evaluation. The proposed 4:2 compressor saves 87.33% of leakage power and is 75.90% more energy efficient compared to its conventional counterpart.

Optimization of Three-Dimensional Blade and Variable Stators for Efficiency and Stability Enhancement of Multistage Axial Flow Compressor at Variable Speeds

Abstract High efficiency and wide stability at variable speeds are equally important to the design and operation of multistage axial flow compressors. However, published research works on three-dimensional design optimization of compressors are so far mainly limited to a single blade row or stage at design speed due to the curse of dimensionality. Moreover, optimization of variable inlet guide vanes (IGV)/stators for off-design operations is carried out by using a rapid but low-fidelity prediction tool and is generally independent of design optimization of blade geometry. To tackle these issues, a three-dimensional holistic design and adjustment optimization method is developed in which both three-dimensional blade geometry and variable IGV/stators are optimized simultaneously for better efficiency and stability at design and off-design conditions. Metamodel-interpreted data mining method and adaptive infilling strategy are used respectively to enhance the capability of the metamodeling and optimization. The developed method is then applied to a modern highly loaded 3.5-stage transonic axial flow compressor at both design and part-design speeds. The results show that the stall margin is extended from 8.23% to 19.65% at 70% design speed while peak efficiency is slightly improved at design speed. The flow mechanisms responsible for the efficiency enhancement at design speed are mainly associated with the reduced total pressure loss in stators as well as inter- and intra-stage loading redistribution. The stability enhancement at 70% design speed is mainly achieved by loading the front blade rows while unloading the limiting rear blade row through variable IGV/stators adjustment. The developed holistic design and adjustment optimization method with the aid of metamodel-interpreted data mining is of great application value for the design and adjustment of advanced multistage axial flow compressors.

Patrik Kovář, Jiří Fürst

In recent years, the flow analysis by means of computational fluid dynamics (CFD) has become a useful design and optimization tool. Unfortunately, despite advances in the computational power, numerical simulations are still very time consuming. Thus, empirical correlation models keep their importance as a tool for early stages of axial compressor design and for prediction of basic performance parameters. These correlations were developed based on experimental data obtained from 2D measurements performed on cases of classical airfoils such as the NACA 65-series or C.4 profiles. There is insufficient amount of experimental data for other families of airfoils, but CFD simulations can be used instead and their results correlated using artificial neural networks (ANN), as described in this work. Unlike the classical deep learning approach using perceptrons, this work presents neural networks employing higher order neural units.

Centrifugal compressor design for high-temperature heat pumps

Heat pumps are identified as crucial technology for decarbonising the heat production. Especially for large-scale, high-temperature heat pumps the use of centrifugal compressors has been seen as an attractive technological option. However, there are very few detailed studies available discussing the compressor designs with different refrigerants for high-temperature heat pumps. This study combines the analyses of a 500 kW two-stage heat pump cycle and centrifugal compressor designs. The study qualitatively assesses the feasibility of compressor designs and provides information on how the dimensions, efficiency, and rotational speed are influenced by cycle conditions and the refrigerant. Temperature lift and evaporation temperature were varied with eight working fluids, including hydrocarbons and hydrofluoro-olefins. The estimated COPs were 2.0–2.55 with the highest values observed with pentane and isopentane. The compressor rotational speeds were between 20 – 50 krpm with hydrocarbons requiring higher values than fluids containing fluorine. The predicted compressor efficiencies were between 77% to 84%, with low pressure compressor reaching higher efficiencies than the high-pressure compressor. However, high compressor Mach numbers were observed, and the Mach number seems to be the main obstacle for the increase of the heat pump temperature lift when centrifugal compressors are used.