Sensitivity Analysis of One-Dimensional Performance Prediction for Centrifugal Compressor

Abstract

To explore the sensitivity sorting of a one-dimensional performance prediction model, a high-load centrifugal compressor is studied. Using the Latin Hypercube method, the influencing factors of the one-dimensional performance prediction model are designed. Based on the sensitivity analysis of ANOVA, the main influencing factors of compressor pressure ratio and efficiency performance are investigated, and guidance for compressor optimization is proposed. The results show that the main factors affecting the pressure ratio are deviation loss, radial diffuser incidence loss, and impeller blockage loss. The main factors affecting the efficiency are radial diffuser incidence loss, radial diffuser blockage loss, and radial diffuser choke loss. Finally, the optimal coefficients corresponding to the loss models are obtained based on the sensitivity sorting results. Compared with the corresponding three-dimensional numerical simulation, the error of pressure ratio and efficiency near the design condition is within 1%, which indicates that the presented method can achieve the accurate design and off-design performance prediction.