An Improved Grey Wolf Optimizer(IGWO) algorithm for optimization of centrifugal pump with guide vane

Abstract To improve the hydraulic performance of a centrifugal pump with guide vane, an improved grey wolf optimizer (IGWO) algorithm is proposed. First, the IGWO algorithm enhances the diversity and global exploration of the initial population with optimal Latin hypercube sampling. Then, the convergence factor is improved by combining the Tanh function to meet the needs of complex non-linear optimization problems. Finally, a search mechanism that enhances population communication is constructed and combined with a mutation-driven search scheme to improve the ability to avoids the local optima traps. The results show that IGWO algorithm has obvious advantages in convergence speed and robustness when dealing with complex non-linear optimization problems. Additionally, satisfactory results are achieved in the application of centrifugal pump optimization. The efficiency of optimized pump reaches 87.8%, which is 1.2% higher than that of the original pump. The anti-cavitation performance of the centrifugal pump is enhanced by improving the distribution of blade inlet attack angles. The vortex area inside the optimized pump impeller is reduced over a large area, and the operating stability of the pump, the matching between the impeller and the guide vane, and the flow characteristics in the guide vane domain are all improved.