Abstract
The spanwise distribution of impeller exit circulation (SDIEC) has a significant effect on the impeller performance, therefore, there is a need for its consideration in the optimization design of mixed-flow pumps. In this study, a combination optimization system, including a 3D inverse design method (IDM), computational fluid dynamics (CFD), Latin hypercube sampling (LHS) method, response surface model (RSM), and non-dominated sorting genetic algorithm (NSGA-Ⅱ) was used to improve the performance of the mixed-flow pump after considering the effect of SDIEC on the performance of the impeller. The CFD results confirm the accuracy and credibility of the optimization results because of the good agreement the CFD results established with the experimental measurements. Compared with the original impeller, the pump efficiency of the preferred impeller at 0.8Qdes, 1.0Qdes, and 1.2Qdes improved by 0.63%, 3.39%, and 3.77% respectively. The low-pressure region on the blade surface reduced by 96.92% while the pump head difference was less than 1.84% at the design point. In addition, a comparison of the flow field of the preferred impeller and the original impeller revealed the effect of SDIEC on mixed-flow pump performance improvement and flow mechanism.
Highlights
The amount of energy consumed by various pumps accounts for more than 12% of the total energy consumption every year
The geometric parameters are used to describe the spatial shape of the impeller; computational fluid dynamics (CFD) is used to calculate the performance of the impeller; design of experiment (DOE) is used to create the database samples; the approximate model is used to construct the function relationship between the design variables and optimization objectives, and the optimization algorithm is used to solve the approximate model to obtain an optimal solution set in the entire design space
The performance estimation of the mixed-flow pump in this optimization process is completed by the CFD calculations
Summary
The amount of energy consumed by various pumps accounts for more than 12% of the total energy consumption every year. The geometric parameters are used to describe the spatial shape of the impeller; CFD is used to calculate the performance of the impeller; DOE is used to create the database samples; the approximate model is used to construct the function relationship between the design variables and optimization objectives, and the optimization algorithm is used to solve the approximate model to obtain an optimal solution set in the entire design space. The effectiveness of this optimization system has been verified in a large number of optimization designs. Kim et al [2], solved the Processes 2020, 8, 905; doi:10.3390/pr8080905 www.mdpi.com/journal/processes
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