期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2012
卷号：15
期号：1
出版社：IOP Publishing
摘要：This paper presents an optimization procedure based on a radial basis neural network surrogate model for design of a vaned diffuser in a mixed -flow pump. Numerical analysis of fluid flo w in a mixed-flow pump has been carried out b y solving three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model. The optimization processes have been performed twice to investigate the coupled effects of diverse variables. The first optimization process has been conducted with two design variables defining the straight vane length ratio and the diffusion area ratio, and the second one has been conducted with four design variables, i.e., the angle at the diffuser vane tip, the distance between the impeller blade trailing edge and the diffuser vane leading edge, and the two design variables used in the first optimization. The efficiency as a hydrodynamic performance parameter has been selected as the objective function for optimizations. The objective function values have been assessed through three-dimensional flow analysis at design points sampled by Latin hypercube sampling in the design space. The first and second optimizations with the coupled effects of diverse variables have yielded maximum increases in efficiency of 7.16% and 9.75%, respectively, compared to the reference shape. The off-design performance has been also improved in most of the optimum shapes except in the shut-off flow region
