Investigating the hydraulic performance of slanted axial flow pumps using an enstrophy dissipation-based hybrid optimization approach

Axial flow pumps (AFPs) are widely employed in urban flood control and drainage systems due to its high discharge at relatively low heads. As off-design condition becomes more common in real operations, we proposed an enstrophy dissipation-based hybrid optimization (EDHO) approach, which combines both the advantage of sparrow search algorithm and Non-dominated Sorting Genetic Algorithm III (NSGA-III) to enlarge the Preferred Operating Range (POR) of a slanted axial flow pump (SAFP). The overall hydraulic performance was optimized with the proposed EDHO approach with a special focus on energy loss mechanism. According to the analysis, eddy dissipation occupied the most energy loss under partial loads, while shear dissipation also contributed a lot under overload conditions especially around impellers. It is demonstrated that the POR of SAFP was significantly improved after optimization. In particular, the available operation interval was broadened, and the corresponding head and efficiency were remarkably increased by refining the impeller and diffuser profiles. In contrast with NSGA-II, NSGA-III, and multi-objective evolutionary algorithm, the novel hybrid algorithm showed significantly better convergence performance, solution diversity, and stability.

Automated summary

An enstrophy dissipation-based hybrid optimization (EDHO) approach, combining the advantages of sparrow search algorithm and Non-dominated Sorting Genetic Algorithm III (NSGA-III), was proposed to enlarge the Preferred Operating Range (POR) of a slanted axial flow pump (SAFP). The overall hydraulic performance was optimized with a special focus on energy loss mechanism. The results showed that eddy dissipation contributed the most energy loss under partial loads, while shear dissipation also played a significant role under overload conditions.