This work presents a three-objective design optimization of a centrifugal pump impeller to reduce flow recirculation and cavitation using three-dimensional (3D) Reynolds-averaged Navier–Stokes equations. A cavitation model was used to simulate the multiphase cavitating flow inside the centrifugal pump. The numerical results were validated by comparing them with experimental data for the total head coefficient and critical cavitation number. To achieve the optimization goals, blockage at 50% of the design flow rate, hydraulic efficiency at the design flow rate, and critical cavitation number for a head-drop of 3% at 125% of the design flow rate were selected as the objective functions. Based on the results of the elementary effect (EE) method, the design variables selected were the axial length of the blade, the control point for the meridional profile of the shroud, the inlet radius of the blade hub, and the incidence angle of tip of the blade. Kriging models were constructed to approximate the objective functions in the design space using the objective function values calculated at the design points selected by Latin hypercube sampling (LHS). Pareto-optimal solutions were obtained using a multi-objective genetic algorithm (MOGA). Six representative Pareto-optimal designs (POD) were analyzed to evaluate the optimization results. The PODs showed large improvements in the objective functions compared to the baseline design. Thus, both the hydraulic performance and the reliability of the centrifugal pump were improved by the optimization.

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