Design Optimization of a Centrifugal Compressor Impeller Using Radial Basis Neural Network Method

Abstract

This paper presents a procedure for design optimization of a centrifugal compressor. The centrifugal compressor consists of a centrifugal impeller, vaneless diffuser and volute. And, optimization techniques based on radial basis neural network method are used to optimize the impeller of the centrifugal compressor. Latin hypercube sampling of design of experiments is used to generate thirty design points within design spaces. Three-dimensional Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the objective function of an isentropic efficiency. Four variables defining impeller hub and shroud contours are selected as design variables in this optimization. The results of optimization show that the isentropic efficiency of the optimized shape at the design flow coefficient is enhanced by 1.0% and the efficiencies at the off-design points are also improved significantly by the design optimization.