Multi-Objective Optimization Method for Performance Prediction Loss Model of Centrifugal Compressors

作     者：ZHANG Lei FENG Xueheng YUAN Wei CHEN Ruilin ZHANG Qian LI Hongyang AN Guangyao LANG Jinhua 

作者机构：Department of Power EngineeringNorth China Electric Power University Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation TechnologyNorth China Electric Power University Baoding Key Laboratory of Low Carbon and High Efficiency Power Generation TechnologyNorth China Electric Power University 

出 版 物：《Journal of Thermal Science》 (热科学学报(英文版))

年 卷 期：2025年第02期

页      面：590-606页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080704[工学-流体机械及工程] 080103[工学-流体力学] 081104[工学-模式识别与智能系统] 08[工学] 0807[工学-动力工程及工程热物理] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0801[工学-力学（可授工学、理学学位）] 

基　　金：supports of National Natural Science Foundation of China (Grant No.52076079) Natural Science Foundation of Hebei Province,China (Grant No.E2020502013) Fundamental Research Funds for the Central Universities, China (Grant No.2021MS079/Grant No.2022MS081) 

摘      要：The selection of loss models has a significant effect on the one-dimensional mean streamline analysis for obtaining the performance of centrifugal *** this study,a set of optimized loss models is proposed based on the classical loss models suggested by Aungier,Coppage,and *** proportions and variation laws of losses predicted by the three sets of models are discussed on the NASA Low-Speed-Centrifugal-Compressor(LSCC) under the mass flow of 22 kg/s to 36 kg/*** results indicate that the weights of Skin friction loss,Diffusion loss,Disk friction loss,Clearance loss,Blade loading loss,Recirculation loss,and Vaneless diffuser loss are greater than 10%,which is dominant for performance ***,these losses are considered in the composition of new loss *** addition,the multi-objective optimization method with the Genetic Algorithm(GA) is applied to the correction of loss coefficients to obtain the final optimization loss *** with the experimental data,the maximum relative error of adiabatic the three classical models is 7.22%,while the maximum relative error calculated by optimized loss models is 1.22%,which is reduced by 6%.Similarly,compared with the original model,the maximum relative error of the total pressure ratio is also *** a result,the present optimized models provide more reliable performance prediction in both tendency and accuracy than the classical loss models.