This work presents a numerical optimization procedure for a low-speed axial flow fan blade with weighted average surrogate model. Reynolds-averaged Navier-Stokes equations with SST turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. The blade profile as well as stacking line is modified to enhance blade total efficiency, i.e., the objective function. Six design variables related to blade lean and blade profile are selected, and a design of experiments technique produces design points where flow analyses are performed to obtain values of the objective function. PBA model is employed as a surrogate model for optimization. A search algorithm is used to find the optimal design in the design space from the constructed surrogate model for the objective function. As a main result, the efficiency is increased effectively by the present optimization procedure.

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