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| Robust optimization design on impeller of mixed-flow pump |
| ZHAO Binjuan1*, LIAO Wenyan1, XIE Yuntong1,HAN Luyao1, FU Yanxia1, HUANG Zhongfu2 |
| 1. School of Energy and Power Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China; 2. School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China |
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Abstract To increase the robustness of the optimization solutions of the mixed-flow pump, the impeller was firstly indirectly parameterized based on the 2D blade design theory. Secondly, the robustness of the optimization solution was mathematically defined, and then calculated by Monte Carlo sampling method. Thirdly, the optimization on the mixed-flow pump′s impeller was decomposed into the optimal and robust sub-optimization problems, to maximize the pump head and efficiency and minimize the fluctuation degree of them under varying working conditions at the same time. Fourthly, using response surface model, a surrogate model was established between the optimization objectives and control variables of the shape of the impeller. Finally, based on a multi-objective genetic optimization algorithm, a two-loop iterative optimization process was designed to find the optimal solution with good robustness. Comparing the original and optimized pump, it is found that the internal flow field of the optimized pump has been improved under various operating conditions, the hydraulic performance has been improved consequently, and the range of high efficient zone has also been widened. Besides, with the changing of working conditions, the change trend of the hydraulic performance of the optimized pump becomes gentler, the flow field distribution is more uniform, and the influence degree of the varia-tion of working conditions decreases, and the operating stability of the pump was improved. It is concluded that the robust optimization method proposed in this paper is a reasonable way to optimize the mixed-flow pump, and provides references for optimization problems of other fluid machinery.
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Received: 27 February 2020
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