Performance optimization of centrifugal pump based on particle swarm optimization and entropy generation theory

Abstract

Centrifugal pumps are frequently utilized in general machinery, but they have issues with low efficiency, unstable operation, and high-power consumption in actual engineering, making performance improvements necessary. In this paper, the particle swarm algorithm is utilized to find the optimal solution among the Pareto front solutions and obtain the most suitable impeller for the centrifugal pump with the lowest entropy generation and highest efficiency as the optimization objectives. Based on the entropy generation theory, the energy losses of the original model and the optimized model are compared and analyzed. The results show that the centrifugal pump impeller and volute are the two areas with the largest entropy generation ratio, the optimized centrifugal pump entropy generation decreases by 5.41%, and the efficiency increases by 3.89%. Turbulent entropy generation and wall entropy generation are the important causes of hydraulic losses. Most of the losses within the impeller occur mainly at leading edge and trailing edge of blade. As the flow rate increases, the closer the distribution of the high entropy generation rate at the front cover of the impeller, the more serious the flow losses. This paper can provide a theoretical reference for the performance optimization of centrifugal pumps.