Numerical shape optimization of a centrifugal pump impeller using artificial bee colony algorithm

Abstract

Centrifugal pumps consume huge amounts of energy in various industrial applications. Therefore for these pumps, the improvement of machine efficiency has become a major challenge. Since the hydraulic performance of a centrifugal pump strictly depends on its impeller shape, in the present work, an efficient and original approach has been developed and applied to the design of centrifugal pump impellers in order to achieve a higher efficiency. A global optimization method based on the Artificial Neural Networks (ANNs) and Artificial Bee Colony (ABC) algorithm has been used along with a validated 3D Navier–Stokes flow solver to redesign the impeller geometry and improve the performance of a Berkeh 32-160 pump as a case study. In the next step, to verify the optimization results, all the domains within the centrifugal pump were simulated using the CFD method. The complete numerical characteristic curves of the pump with the optimized impeller were compared to the validated (using the available experimental data) numerical characteristic curves of the initial pump. The numerical results show an efficiency improvement of 3.59% at only 6.89m increase of total pressure difference for the Berkeh 32-160 centrifugal pump. The new impeller geometry presents much more changes in the meridional channel and blade profile. The results indicate a reasonable improvement in the optimal design of pump impeller and a higher performance using the ABC algorithm.