Volute Optimization Based on Self-Adaption Kriging Surrogate Model

Abstract

Optimizing the volute performance can effectively improve the efficiency of a centrifugal fan by changing the volute geometric parameter, so the self-adaption Kriging surrogate model is used to optimize the volute geometric parameter. Firstly, volute radius Rd, the radius of tongue r, and outlet angle of the volute θ are selected as the optimization parameters of the volute, and latin hypercube sampling is used to configure the initial sample points, the corresponding three-dimensional aerodynamic model under each sample point configuration is constructed. CFD software is used to simulate the aerodynamic efficiency and total pressure of the centrifugal fan under each initial sample point configuration. Secondly, the Kriging surrogate model of initial sample point configuration parameters, aerodynamic efficiency, and total pressure of volute is constructed, and sample points are added by expectation improvement (EI) method to improve the fitting accuracy of Kriging surrogate model. Finally, the high-precision Kriging surrogate model is used as the fitness function of NSGA-II algorithm to find the Pareto optimal solution under multiobjective optimization, and the optimization target are aero dynamical efficiency and total pressure. The rationality of the above method is verified by optimizing the 9–19.4A type centrifugal fan volute. The efficiency of the optimized fan under working conditions is increased by 1%, and the total pressure under working conditions is not reduced. The optimized volute can effectively improve the overall performance of the centrifugal fan. This study is helpful to promote the application of numerical optimization design method in the volute of centrifugal fan. It provides reference for the optimization design of high-performance centrifugal fan.