Performance Prediction Of Centrifugal Compressors Research Articles

Centrifugal compressor performance prediction and dynamic simulation of natural gas hydrogen blended

It is great significant to explore the changes of compressor performance for hydrogen transportation. We found that a Gray-RBF neural network prediction model improved prediction accuracy. The prediction error of the model is 2.34 % by data verification. It was found that the hydrogen blending ratio was increased from 0 % to 30 %, the pipeline transmission power was reduced by 9.3 %. Simultaneously injecting hydrogen to natural gas causes the performance curve of the compressor to shift downwards. The pressure ratio decreases by 18.9 % and shaft power decreases by 28.6 % when the hydrogen blending ratio increases from 0 % to 30 %. The injection of hydrogen to natural gas causes the surge range of the compressor to increase, so the stable range to narrow. In general, this research may provide reference and guidance for the transportation research of hydrogen blended natural gas and compressor operation about gas industry.

Quantitative investigation of the turbulence model effect on high-pressure-ratio centrifugal compressor performance prediction

The accuracy of centrifugal compressors performance and flow field prediction by Computational Fluid Dynamics (CFD) is a serious problem facing in the design and analysis process due to its complex flow feature inside. Different turbulence models choosing in the Reynolds-Averaged Navier-Stokes Equations (RANS) leads to different simulation results. In this paper, a high-pressure-ratio centrifugal compressor was used as the simulation object to discuss the effect of common turbulence models, including a one-equation model (Spalart-Allmaras model), a two-equation linear model (Shear Stress Transport model) and a two-equation nonlinear model (Explicit Algebraic RSM model), on performance prediction under design speed. By introducing the calculation method of local entropy generation rate, an improved method of dividing different types of loss in centrifugal compressors was proposed. After comparing with the experiment results, the effect of turbulence models on loss prediction inside the compressor was quantitative investigated. Further, the flow mechanism underlying was discussed. The results show that the secondary flow loss have the largest impact on the components' prediction performance, also, the reasons for different magnitudes of secondary flow loss inside the impeller and the diffuser are different. These comparisons hope to help designers choose an appropriate turbulence model in further compressor design process and may benefit future turbulence modelling development.

Modification and Validation of 1D Loss Models for the Off-Design Performance Prediction of Centrifugal Compressors with Splitter Blades

One-dimensional (1D) aerodynamic performance predictions are very often conducted by researchers and designers during the preliminary design of centrifugal compressors. This paper focuses on a 1D prediction method for centrifugal compressors with splitter blades, which is rarely seen in the open literature. One-dimensional prediction of aerodynamic overall performance is made for centrifugal compressors with different technical design specifications. However, the aerodynamic overall prediction accuracy relies on the accuracy of the 1D-loss-models used. Therefore, an optimum combination of loss models is proposed by summarizing a variety of loss models presented in the public literature. In addition, an optimization method is utilized to optimize some coefficients involved in loss models in order to improve the generality of the combined model. The modified models obtained in this study are proved to have good predictive accuracy.

Performance prediction of centrifugal compressor based on a new volute loss model and corrected theoretical work

AbstractPerformance prediction plays an important role in the predesign stage of centrifugal compressors. A set of loss models is usually selected and grouped to fulfill the above prediction. To improve the defects of traditional prediction, we modified the outlet velocity and slip coefficient of the impeller by means of the energy average method to obtain theoretical work. A new volute loss model is proposed to replace the traditional semiempirical loss model by adopting a suitable loss model for each flow passage component. A proper performance prediction method is established for the centrifugal compressor studied in this paper. The overall performance of a single‐stage centrifugal compressor is predicted and compared with experimental and numerical simulation results. It is found that the prediction method proposed can better predict the overall performance of the centrifugal compressor. And the volute loss is the third largest loss after impeller loss.

A method to select loss correlations for centrifugal compressor performance prediction

The study reviews the main loss mechanisms and corresponding loss correlations, which are used to predict centrifugal compressor performance. There are one or more loss correlations in the open literature for the same loss mechanism. The purpose of this review is to identify a reliable loss correlation set for centrifugal compressor performance prediction. According to the inlet tip relative Mach number and specific speed, a new method to select loss correlations is proposed by testing multiple loss correlations. This method is validated by experimental results on eight centrifugal compressors in public and one in-house. The performance as-predicted by the proposed method is in close agreement with the experimental results. Compared with the conventional set, the proposed method is superior.

Determination of a suitable set of loss models for centrifugal compressor performance prediction

Performance prediction in preliminary design stages of several turbomachinery components is a critical task in order to bring the design processes of these devices to a successful conclusion. In this paper, a review and analysis of the major loss mechanisms and loss models, used to determine the efficiency of a single stage centrifugal compressor, and a subsequent examination to determine an appropriate loss correlation set for estimating the isentropic efficiency in preliminary design stages of centrifugal compressors, were developed. Several semi-empirical correlations, commonly used to predict the efficiency of centrifugal compressors, were implemented in FORTRAN code and then were compared with experimental results in order to establish a loss correlation set to determine, with good approximation, the isentropic efficiency of single stage compressor. The aim of this study is to provide a suitable loss correlation set for determining the isentropic efficiency of a single stage centrifugal compressor, because, with a large amount of loss mechanisms and correlations available in the literature, it is difficult to ascertain how many and which correlations to employ for the correct prediction of the efficiency in the preliminary stage design of a centrifugal compressor. Asa result of this study, a set of correlations composed by nine loss mechanisms for single stage centrifugal compressors, conformed by a rotor and a diffuser, are specified.

Rapid Modeling Method for Performance Prediction of Centrifugal Compressor Based on Model Migration and SVM

An accurate model is important for design and optimization control of centrifugal compressor. However, due to the varying operation conditions and the complexity of the flow dynamics inside it, establishing a satisfaction model of a new compressor is time and cost consuming. This paper proposes a rapid modeling method for centrifugal compressor based on model migration and support vector machines (SVMs). A general framework for centrifugal compressor model migration is given between two similar compressors, the base model of an existing old compressor is revised to fit for the new compressor by SVM using a small number of data. The effective of the proposed method is contrasted with pure SVM by a simulation case and the results show that, compared with the pure SVM, the migrated model can fit the new compressor faster with better accuracy, which is useful for reducing the cost and time in developing the model for new compressors.

Optimization of Loss Models for Centrifugal Compressor Performance Prediction Based on Numerical Analysis Results

An optimization of loss models for performance prediction of centrifugal compressors has been conducted in this paper. A centrifugal compressor with vaneless diffuser (VLD) and vaned diffuser (VD) is selected for the present study. The study begins with a numerical analysis, using commercial software ANSYS CFX. The numerical result is used to modify mean streamline analysis loss models. Matlab optimization toolbox is used for this purpose. Also, a matlab program is compiled to calculate the off-design performance of the centrifugal compressor. The results show that after optimizating the loss models, mean streamline analysis has a better accuracy than before.

Performance Prediction of Centrifugal Compressor Based on Performance Test, Similarity Conversion and CFD Simulation

One centrifugal compressor is applied for refrigeration and its working substance is R134a. The operating points obtained by using similar conversion at different rotation speeds are compared with the numerical results. They keep consistent with each other while the rotation speeds are lower, but the error between them will become large with the increasing of the rotation speed. Then the operating points are obtained when the working substance is air by using two similar conversion methods separately. Based on the comparison, it can be obtained that the result of keeping the specific volume ratio of inlet and outlet is more accurate than the result of maintaining Ma number. Then the test result is compared with the similarity result and the numerical result when the working substance is air. It is obtained that the similarity result is more consistent with the test result better than the numerical result and the trend of efficiency and pressure ratio change with the flow rate is consistent with the test result. In the process of similar conversion, the efficiency is no useful for similitude design and it has less influence on the conversion result.

Immune Genetic Evolutionary Algorithm of Wavelet Neural Network to Predict the Performance in the Centrifugal Compressor and Research

Prediction of the performance of centrifugal compressors, the traditional methods using BP neural network. This single neural network for forecasting problem is not high enough precision, slow convergence and easy to fall into local optimal solution. In order to more accurately predict the performance of centrifugal compressors, the implicit commit identify problems early. Are the immune algorithm, genetic algorithm, wavelet theory, the combination of neural networks, established immune genetic algorithm optimization of wavelet neural network model (IGA-WNN). Realized to predict the performance of centrifugal compressor, and the predicted results with the BP neural network model prediction results and the wavelet neural network model prediction results were compared. Simulation results show that: the prediction model, can achieve the centrifugal compressor performance prediction and monitoring. Which, IGA-WNN optimal prediction results: with a simple algorithm, structural stability, the convergence speed and generalization ability of the advantages of prediction accuracy of 99% over traditional methods of prediction accuracy of 15%, with a certain Theoretical study and practical value.

Research and Application of Wavelet Neural Networks of Particle Swarm Optimization Algorithm in the Performance Prediction of Centrifugal Compressor

The traditional method of centrifugal compressor performance prediction is usually the BP neural network, however, the problems are that prediction accuracy is not high enough, convergence is slow and it is apt to fall into local optimal solution. In order to predict the performance of centrifugal compressors more accurately and identify the implicit problems in advance, now we combine the particle swarm optimization, wavelet theory and neural networks, to establish performance prediction model of centrifugal compressor based on wavelet neural network of PSO. First, set the various parameters of wavelet neural network as the particle position vector X and the energy function of mean square error as the optimized objective function. By particle swarm optimization algorithm to iterate the basic formula to obtain the corresponding WNN coefficient and then use back-propagation algorithm to train WNN to approach any nonlinear function. Simulation results show that application of the prediction model can achieve the accurate prediction of performance and monitoring of centrifugal compressor. The prediction model has the advantages of simple algorithm, stable structure, fast calculation of convergence speed and strong generalization ability with a prediction accuracy of 99%, 13% higher than prediction accuracy of traditional methods, which has a certain theoretical research value and practical value.

Improving a one-dimensional centrifugal compressor performance prediction method

A one-dimensional centrifugal compressor performance prediction technique that has been available for some time is updated as a result of extracting the component performance from three-dimensional computational fluid dynamic (CFD) analyses. Confidence in the CFD results is provided by comparison of overall performance for one of the compressor examples. The extracted impeller characteristic is compared with the original impeller loss model, and this indicated that some improvement was desirable. The position of least impeller loss was determined using a traditional axial compressor cascade method, and suitable algebraic expressions were derived to match the CFD data. The merit of the approach lies with the relative ease that CFD component performance currently can be achieved and adjusting one-dimensional methods to agree with the CFD-derived models.

Systematic two-zone modelling for performance prediction of centrifugal compressors

This paper presents systematic two-zone modelling for reliable performance prediction of centrifugal compressors. In order to improve the predictive capability, a modified jet slip factor is developed and new corrections for the wake flow deviation and mass fraction are suggested on the basis of the comprehensive experimental data of the three Eckardt impellers. The proposed two-zone modelling is tested against nine sets of measured data of centrifugal compressors. The results are also compared with those obtained by mean streamline analysis. It was found that the predictions by the present two-zone modelling agree fairly well with experimental data for a variety of centrifugal compressors over the wide operating conditions.

Application of Through‐Flow Calculation to Designand Performance Prediction of Centrifugal Compressor

A computer code predicting the flows through the centrifugal compressor with the radial vaneless diffuser was developed and applied to investigate the detailed flowfields, i.e., secondary flows and jet‐wake type flow pattern in design and off‐design conditions. Various parameters such as slip factors, aerodynamic blockages, entropy generation and two‐zone modeling which are widely used in design and performance prediction, were discussed.A control volume method based on a general curvilinear coordinate system was used to solve the time‐averaged Navier–Stokes equations and SIMPLER algorithm was used to solve the pressure linked continuity equation. The standard k − ε turbulence model was used to obtain the eddy viscosity. Performance of the code was verified using the measured data for the Eckardt impeller.

An optimum set of loss models for performance prediction of centrifugal compressors

The present study has tested most of the loss models previously published in the open literature and found an optimum set of empirical loss models for a reliable performance prediction of centrifugal compressors. In order to improve the prediction of efficiency curves, this paper recommends a modified parasitic loss model. The performance analyses by using various empirical loss models are also compared with those by the two-zone modelling. Predicted performance curves by the proposed optimum set agree fairly well with experimental data for a variety of centrifugal compressors. The prediction method developed through this study can serve as a tool for preliminary design and assist the understanding of the operational characteristics of general purpose centrifugal compressors.

Performance prediction and loss analysis of centrifugal compressors

The present study has tested most of loss models previously published in the open literature and found an optimum set of empirical loss models for a reliable performance prediction of centrifugal compressors. In order to improve the prediction of efficiency curves, this paper recommends a modified parasitic loss model. Predicted performance curves by the proposed optimum set agree fairly well with experimental data for a variety of centrifugal compressors. The prediction method developed through this study can serve as a tool for preliminary design and assist the understanding of the operational characteristics of general purpose centrifugal compressors.