Increasing extreme rainfall events caused by global climate change have had a significant impact on urban drainage systems. As a critical component of a pumping station, a large-scale slanted axial-flow pump (SAFP) featuring high specific speed plays a critical role in mitigating urban flooding and waterlogging. In this study, to reveal the transient characteristics of a SAFP at shut-off conditions, a computational fluid dynamics (CFD) based approach with dynamic mesh was proposed. Multiple shut-off conditions with various shut-down speeds of the sluice gate (SG) were modeled. Our analysis demonstrated that both the shut-off conditions and the slanted structure have conspicuous impacts on the hydrodynamic performance of a SAFP. Reducing the shut-down speed leads to a greater reverse flow rate and higher runner speed. The water hammer effect was simulated with different shut-down speeds, increasing the water head by 5.07–10.42 m, the axial force by 163.46–297.06 kN∙m, and the axial moment by 116.05–224.01 kN∙m. Compared with the axial direction, moments in the radial directions were found with more obvious oscillation as a result of stronger rotor–stator interaction. Due to the gravitational effect of the slanted structure, the fluctuation of the runner in vertical direction presented an off-axis characteristic compared with the horizontal one. As the SG speed increased, pressure fluctuations gradually decreased at various locations across the SAFP.
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-ΙΙΙ) 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.
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