Compressor Performance Research Articles

Influence of bleeding positions in self-recirculating casing treatments on the stability of a subsonic axial compressor

Influence of bleeding positions in self-recirculating casing treatments on the stability of a subsonic axial compressor

Performance comparison of liquid, vapor, and liquid–vapor injection of single-screw compressor for an air-source heat pump

Refrigerant injection techniques are usually proposed to improve the performance and reliability of compressors when a single-screw compressor applied to an air-source heat pump works at low temperatures in winter. In this study, an experimental study was conducted to present the performance comparison of the single-screw compressor in the air-source heat pump under liquid, vapor, and liquid–vapor refrigerant injection at evaporation temperatures between −19 and −8 °C. The results indicate that, when the evaporation temperature decreases from −8 to −19 °C, the heating capacity under liquid–vapor and vapor injection increases by 16.7% and 12.7%, respectively, compared with that under liquid injection and that the COPh increment under liquid–vapor injection and vapor injection is, respectively, from 11.23% to 39.21% and from 17.18% to 30.82% compared with that under liquid injection. Therefore, the liquid–vapor injection method is conducive to the operation of the air-source heat pump at a lower ambient temperature. The experimental results can provide the basis for the future design of single-screw compressors applied to air-source heat pumps.

Experimental characterization and numerical modelling of an air to water CO2 heat pump under different outdoor and operating conditions for domestic hot water generation

This work assesses the influence of different outdoor and operating conditions on the performance of an air-to-water CO2 heat pump for domestic hot water (DHW) generation. For that purpose, an air to water CO2 heat pump with internal heat exchanger (IHX) was developed and characterized in an experimental campaign under well-controlled lab conditions. The system includes an in-house control system implemented to operate at the optimal gas cooler pressure. The heat pump and the control system are tested for DHW generation. The heat pump uses a finned-tubes heat exchanger as evaporator and plate heat exchangers as gas cooler and internal heat exchanger. The numerical model used a 1dimensional, cell by cell discretization method to characterize the performance of both, the gas-cooler and the evaporator under a wide range of values of their key variables. The IHX is also modelled with the same strategy. ARHI equations are considered to describe the compressor performance. The experimental data obtained are used to validate a numerical model of the heat pump under different air velocities, air temperatures and air humidity at the evaporator. The effectiveness of the control system proposed is experimentally confirmed during the experimental tests. Results show a good agreement between the numerical simulations and the experimental data what permits to validate the model and to assess the performance of the transcritical heat pump under different climate conditions.

Influence of real gas properties on aerodynamic stability of a SCO2 centrifugal compressor

The safe operation of closed-Bryton-cycle system is hindered by the nonlinear real gas properties in a supercritical carbon dioxide (SCO2) centrifugal compressor for waste heat recovery in a powertrain system. This paper aims to understand the influence of real gas properties on the aerodynamic stability of a shrouded SCO2 centrifugal compressor designed for waste heat recovery. Firstly, the numerical method was calibrated and validated using experimental results from the Sandia SCO2 centrifugal compressor. Next, based on the numerical method, the stability performance of an inhouse-design shrouded SCO2 compressor was discussed through a direct comparison with the identical compressor using air. The results showed that the performance of the SCO2 compressor was significantly different from that of the air compressor. Particularly, the impeller was the most unstable component featuring a notable recirculating region near the shroud at the leading edge. Further analysis is carried out to understand the discrepancies in the stability performance between the two compressors with different fluids. It is revealed that the boundary layer on the SCO2 impeller suction surface thickens at a faster rate, leading to stronger flow separation. Meanwhile, the stronger accumulation of low-momentum secondary flow near the SCO2 impeller outlet enhances the ‘wake’ structure near the shroud of suction surface at the impeller tailing edge, resulting in considerable backflow. The different behaviors of boundary layer were attributed to pressure gradient normal to the suction surface. Specifically, the pressure gradient on the suction surface for SCO2 impeller is orders of magnitude higher than that of the air impeller. The stronger gradient weakens momentum exchange in the boundary layer, thus increasing the thickness of boundary layer more rapidly along the streamwise direction. Moreover, the boundary layer is pushed towards the shroud of suction surface by the strong pressure gradient, resulting in the evident accumulation of secondary flow nearby. At the meantime, the low-momentum flow near the impeller outlet reduced the inlet flow velocity of the diffuser, causing more recirculation at the top of the vaneless diffuser in all circumferential directions, thus worsening its instability.

Improved Error-Based Ensemble Learning Model for Compressor Performance Parameter Prediction

Large compressors have complex structures and constantly changing operating conditions. It is challenging to build physical models of compressors to analyse their performance parameters. An improved error-based stacked ensemble learning prediction model is proposed in this work. This model simplifies the modelling steps in a data-driven manner and obtains accurate prediction results. An enhanced integrated model employs K-fold cross-validation to assign dataset weights based on validation set errors, achieving a 12.4% reduction in average output error. Additionally, the output error of the meta-model undergoes a Box–Cox transformation for error compensation, decreasing the average output error by 14.0%. The Stacking model, combining the above improvements, notably reduces the root-mean-square errors for power, surge, and blocking boundaries by 24.2%, 20.6%, and 23.3%, respectively. This integration significantly boosts prediction accuracy.

Investigation on Aerodynamic Performance of a Centrifugal Compressor with Leaned and Bowed 3D Blades

The application of centrifugal compressors is extensive in industries such as aerospace and energy. The blade is the primary factor affecting the aerodynamic performance of compressors. In this paper, the aerodynamic performance of a centrifugal compressor with leaned and bowed 3D blades is investigated. The spanwise section profiles of the blade in the circumferential direction are deflected at different angles, resulting in four compressors with distinct leaned and bowed 3D blades based on the original model. There is a significant change in isentropic efficiency of the modified models under design conditions. Specifically, models 1, 3, and 4 experienced an increase of 0.97%, 1.04%, and 0.79%, respectively, while model 2 experienced a decrease of 0.70%. The profile of the blade tip and 50% spanwise section are shifted towards the suction surface, resulting in a geometric structure where the blade is concave towards the pressure surface. This structure gradually lifts the flow from the blade root to the blade tip downstream to the outlet area of the flow channel, reducing the load on the trailing edge of the blade and making the flow more closely aligned with the blade. At the same time, the larger radial velocity gradient near the blade tip suppresses the backflow on the shroud side, making the flow at the impeller outlet more stable. The outlet velocity of the impeller is more evenly distributed along the spanwise and circumferential directions, which improves the flow at the inlet of the diffuser and enhances the efficiency of the diffuser. Due to the high spanwise height of the leading edge of the blade, this bowed blade structure has little effect on the spanwise curvature upstream of the blade, resulting in negligible influence on the flow of the upstream channel.

Performance assessment and optimisation of a concentric two-piston compressor system for hydrogen storage

The ionic compressor has a prospective application potential for the conversion of mechanical energy into internal energy in high-pressure hydrogen as the ionic liquid can separate the metal piston and the hydrogen gas. The sloshing of the liquid inside is inevitable in such a liquid piston compressor, which has an impact on the specific energy consumption of the hydrogen compression. The thermofluid behaviour of this liquid sloshing can be effectively influenced by the baffle structure and piston trajectory. A novel concentric two-piston compressor is proposed in this paper, which has a unique structure that can act as a baffle inside and actively influences the fluid flow by adjusting the piston trajectory. The quantitative influence of key structural design factors on the compressor performance is investigated by mathematical modelling, based on which the optimal structural design was obtained by Taguchi and analysis of variance methods. Results indicate that the diameter ratio of Piston A to Piston B is the dominating factor for both the mass delivered and the specific energy consumption. With the optimal design in the structure, the specific energy consumption is found as 2328.49 kJ/kg, where the mass delivered and power consumption are observed as 21.42 kg/h and 13.86 kW, respectively.

Geometric and thermodynamic analysis of a fully meshed double-scroll compressor

The double-scroll wrap can effectively increase the volume flow rate compared with the commonly used single-scroll structure, but its built-in volume ratio is extensively reduced. With the aim of improving its built-in volume ratio, this study presented a fully meshed double-scroll profile, or called modified double-scroll, and proposed a generation method for it; its profile equations as well as relationships between its geometric parameters were obtained, and effects of the geometric parameters on the compressor performance were analyzed. Moreover, thermodynamic characteristic and working process of the double-scroll compressor were numerically simulated and verified with its performance experiment. It is found that the proposed fully meshed double-scroll significantly increases the built-in volume ratio by 33.8 %; meanwhile, it increases the volume flow rate, reduces the friction velocity between the orbiting and fixed scrolls, and decreases scroll dimensions. The proposed fully meshed double-scroll can be applied to the design and manufacture of scroll compressors.

Experimental Analysis of the Time-Wise Compressor Fouling Phenomenon

Abstract Compressor fouling is still an unforeseen phenomenon. Gas turbines for heavy-duty and propulsion applications are subject to performance degradation due to fouling, erosion, and corrosion mechanisms. Unlike the last two, the fouling phenomenon is recoverable depending on weather, operating conditions, and operator actions. It is generated by the adhesion of micro-sized particles on the relevant surfaces, generating blade shape and surface roughness variations. Fouling could affect the machine performance differently. The interaction between machine characteristics, airborne contaminants, and environmental conditions determines fouling prediction challenges. An experimental campaign has been carried out in the present analysis to study the overtime modification of compressor performance and mass deposits on the blade and vane surfaces. The axial unit has been operated to control the performance and deposition process by keeping the contamination and the relative humidity constant during the time. The test matrix has been based on two relative humidity values and four exposure time intervals. The results have shown the action of the competitive phenomena as adhesion and detachment, generating a non-linear trend of the deposited mass−time relation depending on impact characteristics and humidity values. Compressor performance follows similar behavior and shows a non-linear trend instead of constant contamination. Data interpretation and generalization are reported to increase the possibility of better predicting the effects of particle adhesion on gas turbine performance degradation.

An Improved Body Force Model to Simulate Blade Loading Variation Under Various Operating Conditions in Transonic Axial Flow Compressor

Abstract In order to analyze the unsteady aerodynamic response of compressors with limited computational resources, the development of the body force (BF) model has been pursued for decades. This model can simulate the effects of the compressor blade on the flow by applying a three-dimensional (3D) force field. Indeed, the accuracy of the BF model simulation highly depends on the construction strategy of BF field. However, for a transonic compressor, the influence of shock waves on the spatial distribution of blade loading is significant, which makes the construction of an appropriate BF field challenging. To solve this issue, an accurate BF model is proposed to describe the effects of the blade on the flow with high spatial fidelity in transonic compressors. For verification, a typical transonic fan rotor, NASA-Rotor 67, is selected. The numerical results calculated by the new BF model are compared with those obtained by the Reynolds-averaged Navier–Stokes (RANS) solver. According to the results, the new model can accurately capture the distribution of blade loading in the transonic blade channel at various operating conditions, eventually leading to a good prediction of compressor performance and the radial distribution of flow parameters downstream of the rotor. Moreover, this study discusses the causes of modeling errors and presents the application of the model in inlet distortion simulation at the end.

Experimental Performance Comparison of High-Glide Hydrocarbon and Synthetic Refrigerant Mixtures in a High-Temperature Heat Pump

Several theoretical studies have predicted that refrigerant mixtures with glides of more than 20 K can yield COP improvements in heat pumps for operating conditions where the temperature difference between the heat source and heat sink is large, but experimental validations and quantifications are scarce. The application of high-glide mixtures (>20 K) in industrial heat pumps in the field is, therefore, still hampered by concerns about the behavior and handling of the mixtures. This study experimentally investigates hydrocarbon (HC) mixtures R-290/600 (propane/butane) and R-290/601 (propane/pentane) and compares them to previously tested mixtures of synthetic refrigerants. Comprehensive evaluations are presented regarding COP, compressor performance, pressure drop, heat transfer, and the possibility of inline composition determination. The mixtures were tested over a range of compositions at a source inlet temperature of 60 °C and a sink outlet temperature of 100 °C, with the heat sink and heat source temperature differences controlled to 35 K. R-290/601 at a mass composition of 70%/30% was found as the best mixture with a COP improvement of 19% over R-600 as the best pure fluid. The overall isentropic compressor efficiency was similar for HC and synthetic refrigerants, given equal suction and discharge pressures. Pressure drops in heat exchangers and connecting lines were equal for synthetic and HC mixtures at equal mass flow rates. This allows higher heating capacities of HC mixtures at a given pressure drop (mass flow rate) due to their wider vapor dome. A previously developed evaporator heat transfer correlation for synthetic refrigerant mixtures was applicable to the HC mixtures. A condenser heat transfer correlation previously fitted for synthetic refrigerants performed significantly worse for HC mixtures. Composition determination during operation and without sampling was possible with a deviation of at most 0.05 mass fraction using simple temperature and pressure measurements and REFPROP for thermodynamic property calculations. Overall, high-glide HC mixtures, just like mixtures of synthetic refrigerants, showed significant COP improvements for specific operating conditions despite a decreased heat transfer coefficient. Potential problems like composition shift or poor compressor performance were not encountered. As a next step, testing high-glide mixtures in pilot-plant installations is recommended.

Predictive Control Scheme for Fuel Cell Air Compressor Efficiency Enhancement with Surge‐ and Choke‐Constrained Awareness

AbstractThe efficiency and dynamic response of air compressors are crucial for stability and lifespan of hydrogen fuel cells. A predictive control scheme with surge‐ and choke‐constrained awareness is proposed to ensure safe and efficient operation of air compressors in this study. The proposed scheme consists of an efficiency enhancement model predictive control (EE‐MPC), and an improved active disturbance rejection control (IADRC). Surge‐ and choke‐constrained awareness is achieved by comparing predicted air flow with surge and choke limitations. Simultaneously, the EE‐MPC is constrained with oxygen excess ratio (OER) and obtains optimal solution by searching active set. The reference flow and supply manifold pressure trajectories for IADRC are generated by EE‐MPC. A designed piecewise differentiable nonlinear smoothing function is embedded in IADRC. The disturbances are estimated for coordinating flow and pressure control. Under China heavy‐duty commercial vehicle test cycle for bus conditions, root‐mean‐squared errors (RMSEs) of flow and pressure are 3.27 g s−1 and 1.88 × 103 Pa, respectively, and the mean efficiency can be enhanced by 13.4% compared to the MPC with fixed OER. Finally, a controller hardware‐in‐the‐loop test is conducted, with flow and pressure RMSEs of 2.48 g s−1 and 4.28 × 103 Pa between the test and simulation, respectively.

Optimisation of design parameters for a novel two-piston ionic compressor applied in hydrogen storage

The ionic compressor is an advanced and prospective compression technology for hydrogen storage. However, a complex wave phenomenon was observed inside the compression chamber due to the fluid flow vortex. This complex gas-fluid interaction can be intervened by a new mechanical design of the motion piston. In this paper, the thermodynamic performance of a novel homocentric two-piston ionic compressor was carried out by mathematical modelling of one compression cycle. The optimisation of the design parameters of the compressor proposed was conducted by the Taguchi method. This study found that the piston diameter ratio was the dominating factor accounting for more than 80 % of the contribution to the mass delivered, power consumption and specific energy consumption. The optimal design parameters were obtained as 0.7 for the piston diameter ratio, 0.5 for the stroke diameter ratio of Piston A and 0.1 for the trajectory parameter. Under the optimal design parameters, the specific energy consumption was obtained as 1563.38 kJ/kg.

The Design and Optimization of Additively Manufactured Radial Compressor of a Miniature Gas Turbine Engine

Abstract This paper presents a multidisciplinary design methodology for a single-stage radial compressor of a small-scale gas turbine jet engine. The entire engine, producing more than 600 N thrust with an engine diameter of less than 30 cm, will be manufactured by additive manufacturing (AM) in a single piece. Therefore, it is crucial to pinpoint the design limitations that may arise due to the AM methods. The preliminary design calculations are carried out in the Von Karman Institute for Fluid Dynamics (VKI's) in-house centrifugal compressor off-design (CCOD) code. The detailed design and optimization studies coupled with computational fluid dynamics (CFD) simulations are performed to improve the aerodynamic performance of the radial compressor by using the sequential quadratic programming (SQP) method with an Adjoint solver in the VKI's in-house computer aided design and optimization (CADO) tool. In the final design, a large increase in thrust is obtained and the manufacturing constraints are satisfied.

A New Global Gas Dynamics Performance Optimization Method for Refrigeration Centrifugal Compressor Stage Based on the Immune Algorithm

Abstract This study proposes a new global gas dynamics optimization method, which was applied to a multi-objective optimization task of centrifugal compressor performance with the aim of determining the improvement probability for achieving high efficiency across a wide operating range. Initially, the original nondominated neighbor immune algorithm (NNIA) was extended to solve constrained multi-objective optimization problems for the first time, which mainly incorporated a procedure for handling inequality and equality constraints without additional parameters. Subsequently, an adaptive topological back-propagation multilayer feed-forward artificial neural network (BP-MLFANN) was trained using the modified NNIA to quickly evaluate the fitness value of the centrifugal compressor stage performance during the optimization. The feasibility of the method was validated using the first stage of a refrigeration centrifugal compressor. The results indicated a substantial enhancement in the stage efficiency of the optimized impeller at the Near-stall, Design, and Near-choke operating points, with increasement of 1.8%, 1.9%, and 4%, respectively, as compared to the baseline stage. The flow field analysis shows that the impact loss at impeller leading edge and flow separation in the passage reduced greatly, the mixing process between the leakage flow and mainstream in the channel is significantly weakened, thus the flow field becomes more uniform after optimization. The new global gas dynamics optimization method provides a reference for the development of efficient and rapid optimization techniques for centrifugal compressor.

Experimental Analysis of Twin Screw Compressor's Energetic Efficiency Depending on Volume Ratio

The current paper presents the results of the experimental analysis to assess and optimize the twin-screw compressor’s efficiency by varying the volume ratio. The experimental tests are conducted on the compressor's test bench, with a dedicated automation system inside the control console. The control and monitoring software allows parameter recording for subsequent visualization, data curation, and post-processing. The evaluation of screw compressor's performance requires a simultaneous analysis of the thermodynamic and flow processes, both of which depend on the compressor’s geometry. The obtained volumetric and adiabatic efficiencies are good, with values over 0.88 and 0.69, respectively.

Detection of Rotating Stall Inception of Axial Compressors Based on Deep Dilated Causal Convolutional Neural Networks

The anomaly detection of outliers and fault diagnosis in the imperfect time-series data is crucial in aero-engine industry. Early detection of the rotating stall is significant for the active stabilization control of the axial compressors, because the rotating stall and surge can cause enormous vibratory stresses in the blades and gives rise to surge to limit the performance of compressors. An aerodynamic instability inception and short-length-scale periodic anomaly prior to stall onset known as stall inception in axial compressors is observed in aero-engine. Based on deep learning theory, this paper conducts the accurate and rapid detection of stall precursors based on deep neural network. The deep dilated causal convolutional neural network combined with logistic regression(LR) named as LR-WaveNet is applied to the detection and prediction of stall inception in the imperfect time-series data of axial compressors with the rotating stall. The LR-WaveNet model can implement fast anomaly detection and stall prediction in long-time term series data. Furthermore, a single LR-WaveNet can be trained to capture and learn the time-domain statistical characteristics of many different stall inception training data with equal fidelity. The trained LR-WaveNet model can rapidly detect the occurrence of anomaly point and predict the probability of rotating stall and surge in axial compressors as an early warning signal. By comparing with the time domain analysis and the wavelet analysis, the calculation results are represented with experimental data to show the effectiveness and feasibility of the stall detection approach based on LR-WaveNet. Especially, the LR-WaveNet can detect the irregular and imperfect stall inception and capture the small fault features when the characteristics of stall inception sigals or data are not very unobvious, irregular and imperfect. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Note to Practitioners–This paper was motivated by the problem of detecting the stall and surge of axial compressor for aeroengine, but it also applies to other small fault diagnosis with imperfect data or time series prediction problem. The stall Inception is very difficult to detect for the reason of imperfect data with small fault or features. These existing detection methods of stall inception can only be applied under certain conditions, because they can only extract the pre-stall features partly. Meanwhile, the excessive number of compressor sensors is demanded in this method, so the application of these traditional methods are limited in practical situations in the stall inception detection. This paper suggests a new approach using Deep Dilated Causal Convolutional Neural Networks. The deep dilated causal convolutional neural network combined with logistic regression(LR) named as LR-WaveNet is applied to the detection and prediction of stall inception in the imperfect time-series data of axial compressors with the rotating stall. In this paper, the new approach is proved to be suitable and feasible to all the types of stall inception including the irregular stall inception with imperfect data. We then show how the deep learning method can be efficiently applied in the imperfect data situation with small fault and time series prediction. The experiments suggest that this approach is feasible. In future research, we will create the novel approach and theory for the detection of stall inception and small fault diagnostics with the imperfect data.

Parametric analysis of the oil pressure limiter built on the influence on the diaphragm compressors for hydrogen refueling stations

The oil pressure limiter is crucial for ensuring the steady operation of the diaphragm compressor, but there is a lack of systematic research on its design method. This study conducted a theoretical analysis of the operation characteristics of the oil pressure limiter in diaphragm compressors, and established a simulation model. Furthermore, a test rig for the oil system of a 90 MPa diaphragm compressor was built to verify the accuracy of the model. The results indicated that the simulated oil pressure curve was in good agreement with the measured curve during the oil overflow process, which confirmed the reliability of the model used to study the oil pressure limiter. The study found that the operational stability of the pressure limiter was significantly influenced by the spring stiffness and valve ball diameter. The oil overflow pressure of the compressor could be made more precise and stable by increasing the valve ball diameter, but the structural size should also be sensible.

Geometric modeling and performance analysis of a combined algebraic spiral scroll compressor

This study proposed a combined algebraic spiral (CAS) scroll compressor with a profile that consists of two algebraic spirals with different parameters smoothly connected by a higher-order curve. The advantage lies in the ability of the ending algebraic spiral to regulate the stroke volume and wrap size, while the starting algebraic spiral can control the discharge volume and the center part of the wrap, thus improving the geometric performance of the scroll compressor. The research established the geometric model of CAS scroll wrap and conducted parametric studies. The results indicate that CAS scroll compressor exhibits the minimum discharge volume, maximum stroke volume, and compression ratio when both the discharge volume chamber and the stroke volume chamber are entirely constructed using the algebraic spiral. Moreover, it was observed that the radial leakage curve length decreases as the polar angle at the connection point increases. Under identical wrap diameters and adequate minimum wall thickness, a larger spiral coefficient may be chosen for the ending algebraic spiral in order to enhance geometric performance. Conversely, a smaller spiral coefficient and spiral index for the starting algebraic spiral can improve compression and reduce leakage. Moreover, in comparison to a single algebraic spiral scroll compressor with an equivalent wrap size, CAS scroll compressor exhibits a 20.62% decrease in discharge volume, a 31.62% rise in compression ratio, a 30.75% reduction in radial leakage curve length, and superior geometric performance when compared to other algebraic spiral scroll compressors.

Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary algorithm

As a pivotal part of cathode air supply system, centrifugal air compressors play a central position in ensuring efficient operations of onboard fuel cells. To improve the overall performance of compressors, comprehensive performance tests were conducted and an integrated simulation model was developed by using computational fluid dynamics (CFD) methods. On this basis, the prediction performance of Linear-based Boosting models was investigated, and multi-objective optimization of impeller structural parameters was carried out through the Reference Vector Guided Evolutionary Algorithm (RVEA). Simulation results indicate that the impeller of the original compressor exhibits significant entropy increase, insufficient gas compression and serious energy dissipation, highlighting considerable room for design optimization. The eXtreme Gradient Boosting (XGBoost) model with 29 estimators has superior generalization ability and prediction performance, making it the preferred Boosting model for the compressor. Multi-objective optimizations have strong universality and rationality, resulting in a well-distributed and diversified final non-dominated solution set. The isentropic efficiency and pressure ratio of the Max_σ solution are improved by 18.7% and 70.1%, while those of the Max_ηc solution are enhanced by 23.0% and 48.9%, respectively. After optimization, the gas experiences reduced shock loss, diminished entropy increase and enhanced flow stability. These findings can provide data support, theoretical basis and directional guidance for performance improvement of centrifugal air compressors.