This paper presents an optimization procedure for high-efficiency design of a vane diffuser in a mixed-flow pump. Optimization techniques based on a radial basis neural network model are used to improve the performance of a vane diffuser in a mixed-flow pump. In flow analyses, three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the efficiency as the objective function. The numerical results are validated through a comparison with experimental data for the head, power and efficiency. Latin-hypercube sampling method as design-of-experiments is used to generate the design points within the design space. In order to improve the efficiency of a mixed-flow pump, four variables defining the lean angle at diffuser vane tip span, the distance between trailing edge of impeller blade and leading edge of diffuser vane, the straight vane length ratio, and the diffusion area ratio are selected as design variables in the present optimization. As a result of the present study, the efficiency at the design point is remarkably enhanced through the design optimization.

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