Multi-objective optimization method for hydraulic performance of centrifugal pumps based on CFD

This study examines the impact of recent multi-objective optimization algorithms on the hydraulic performance (head and efficiency) of centrifugal pumps. Numerical simulations were performed using STAR-CCM + to build the CFD database under varying rotational speeds, flow rates, blade numbers, and stagger angles. A surrogate model based on response surface methodology (RSM) was developed to establish correlations between these parameters and hydraulic performance. The RSM-based optimization was conducted at the rated rotational speed of 3500 r/min, with rotational speed fixed and inlet flow rate, blade number, and blade angle used as the optimization variables. Four optimization algorithms—NSGA-II, NGO, GRO, and HBA—were applied to enhance pump head and efficiency. The optimization algorithms were tuned for the present pump design problem and compared under identical design variables, constraints, and objective functions. The results show that all four algorithms improved the hydraulic performance of the pump. GRO achieved the largest head improvement of 11%, while NGO and HBA showed the highest efficiency improvement of 5%. Among them, HBA provided a balanced improvement, with a 7% increase in pump head and a 5% improvement in efficiency.