采用近似模型和NSGA-Ⅱ遗传算法的旋流泵性能优化研究
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摘要
旋流泵无叶腔宽度、叶片数和叶片宽度是影响旋流泵性能中最重要的几何参数。【目的】建立旋流泵性能优化方法,为今后的工程提供参考。【方法】采用中心复合的方法对无叶腔宽度L、叶片数Z和叶片出口宽度b2进行了试验设计,使用CFD数值计算获得了样本的性能特性,而后采用Kriging模型建立了几何参数与旋流泵效率和叶片表面剪切应力的关系,最后利用非支配排序遗传算法对几何参数进行多目标寻优并进行了性能预测和对比分析。【结果】研究确定旋流泵最优几何参数L为25 mm、Z为8枚、b2为26.45 mm;优化后旋流泵无叶腔的宽度降低了16.67%,叶轮的叶片数增加了1枚,叶片的出口宽度增加了25.95%。优化后旋流泵的效率显著提高,同时叶片的表面剪切应力降低;在设计工况点,旋流泵的效率提高了1.06%,叶片平均剪切应力从优化前的274.37 Pa减少至204.57 Pa,降低了25.44%;优化后消除了在叶片的前缘处较大的剪切应力;叶片的表面的剪切应力在靠近叶片的出口处得到显著抑制。【结论】通过数值模拟验证了中心复合的方法是可行,提高了旋流泵性能。
【Objective】The cavity width L, blade width b2 and the number of blades Z are the most important geometric parameters affecting the performance of vortex pump. This paper aims to present a method to optimize the vortex pump.【Method】The study was based on approximate model and the non-dominated sorting genetic algorithm II(NSGA-II), in which the pump cavity length, blade width and the number of blades were calculated using the central composite design of DoE(design of experiment). The performance of the designed pump was examined using CFD, and the effect of L, b2 and Z on vortex pump efficiency and shear stress on the blade wall was calculated using the Kriging model. The NSGA-II was used to optimize the geometric parameters.【Result】The optimal parameters calculated from the methods were L=25 mm, Z=8, b2=26.45 mm.【Conclusion】We proved that CFD and NSGA-II can be used in a combination to calculate the optimal parameters of the vortex pump, and they can significantly improve efficiency of the pump and reduce the shear stress on the blade. Our results revealed that the optimization can reduce the width of the non-blade cavity by 16.67%, and increase the number of blades of the impeller and the outlet width of the blade by 1 and 25.95% respectively. At the design flow rate, the optimal design increased pump efficiency by 1.06% and reduced the average shear stress on the blade from 274.37 Pa to 204.57 Pa. The optimal design made the shear stress on the blade more uniform, in addition to reducing the shear stress on the outlet of the blade.
【Objective】The cavity width L, blade width b2 and the number of blades Z are the most important geometric parameters affecting the performance of vortex pump. This paper aims to present a method to optimize the vortex pump.【Method】The study was based on approximate model and the non-dominated sorting genetic algorithm II(NSGA-II), in which the pump cavity length, blade width and the number of blades were calculated using the central composite design of DoE(design of experiment). The performance of the designed pump was examined using CFD, and the effect of L, b2 and Z on vortex pump efficiency and shear stress on the blade wall was calculated using the Kriging model. The NSGA-II was used to optimize the geometric parameters.【Result】The optimal parameters calculated from the methods were L=25 mm, Z=8, b2=26.45 mm.【Conclusion】We proved that CFD and NSGA-II can be used in a combination to calculate the optimal parameters of the vortex pump, and they can significantly improve efficiency of the pump and reduce the shear stress on the blade. Our results revealed that the optimization can reduce the width of the non-blade cavity by 16.67%, and increase the number of blades of the impeller and the outlet width of the blade by 1 and 25.95% respectively. At the design flow rate, the optimal design increased pump efficiency by 1.06% and reduced the average shear stress on the blade from 274.37 Pa to 204.57 Pa. The optimal design made the shear stress on the blade more uniform, in addition to reducing the shear stress on the outlet of the blade.
引文
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[12]郑铭,袁寿其.旋流泵结构参数对泵性能的影响[J].农业机械学报, 2000, 31(2):46-49.
[13] AHMAD NOURBAKHSH, HAMED SAFIKHANI, SHAHRAM DERAKHSHAN. The comparison of multi-objective particle swarm optimization and NSGA II algorithm:applications in centrifugal pumps[J]. Engineering Optimization, 2011, 43(10):1 095-1 113.
[14] ZHANG Y, HU S, WU J, et al. Multi-objective optimization of double suction centrifugal pump using Kriging metamodels[J]. Advances in Engineering Software, 2014, 74(4):16-26.
[15] ZHANG Y, HU S, WU J. Modeling and multi-objective optimization of double suction centrifugal pump based on Kriging Meta-models[M]. Advances in Global Optimization., 2015(1):251-261.
[16] ESTECO Inc. modeFRONTIER 2016[CP]. ESTECO Inc, Italy, 2016.
[17]赵选民.试验设计方法[M].北京：科学出版社, 2006.
[18]万伦，宋文武，符杰.隔舌安放角对中比转速离心泵非定常性能的影响[J].灌溉排水学报, 2018, 37(9):86-92.
[19]高红艳,魏占民.镫口扬水灌区输水干渠来沙特性解析[J].灌溉排水学报, 2018,37(7):99-105.
[20]陈雪丽,魏正英,马睿佳,等.灌溉输水管道沟槽减阻研究[J].灌溉排水学报, 2018, 37(3):90-95.
[21]高振军,李浩,刘建瑞,等.回流孔径对磁力驱动离心泵内部流动的影响分析[J].灌溉排水学报, 2017, 36(11):70-78.
[22] ANSYS Inc. ANSYS CFX, Release 17.0[CP]. ANSYS Inc, USA, 2017.
[2] SCHIVLEY G P, DUSSOURD J L. An Analytical and Experimental Study of a Vortex Pump[J]. Journal of Fluids Engineering, 1970, 92(4):889-890.
[3]李世煌,封俊.旋流泵的研究现状及其发展建议[J].北京农业工程大学学报, 1987(3):1-6.
[4]权辉,傅百恒,李仁年.旋流泵的研究现状及发展趋势[J].流体机械, 2016, 44(9):36-40.
[5]刘天宝,赵万勇,李易松.旋流泵的研究现状与展望[J].流体机械, 2007, 35(1):32-36.
[6]汪永志,施卫东,董颖.旋流泵的研究现状与展望[J].排灌机械工程学报, 2004, 22(2):8-11.
[7]黄道见,关醒凡.旋流泵模型实验研究[J].水泵技术, 2002(2):30-31.
[8]沙毅,杨敏官,康灿.旋流泵的特性分析与设计方法探讨[J].农业工程学报, 2004, 20(1):124-127.
[9]沙毅,刘祥松.旋流泵固液两相流输送特性试验[J].农业工程学报, 2013, 29(22):76-82.
[10]沙毅,杨敏官,康灿.污水渣浆旋流泵设计及特性试验[J].江苏大学学报(自然科学版), 2005, 26(2):153-157.
[11]高雄发,施卫东,张德胜.基于CFD正交试验的旋流泵优化设计与试验[J].农业机械学报, 2014, 45(5):101-106.
[12]郑铭,袁寿其.旋流泵结构参数对泵性能的影响[J].农业机械学报, 2000, 31(2):46-49.
[13] AHMAD NOURBAKHSH, HAMED SAFIKHANI, SHAHRAM DERAKHSHAN. The comparison of multi-objective particle swarm optimization and NSGA II algorithm:applications in centrifugal pumps[J]. Engineering Optimization, 2011, 43(10):1 095-1 113.
[14] ZHANG Y, HU S, WU J, et al. Multi-objective optimization of double suction centrifugal pump using Kriging metamodels[J]. Advances in Engineering Software, 2014, 74(4):16-26.
[15] ZHANG Y, HU S, WU J. Modeling and multi-objective optimization of double suction centrifugal pump based on Kriging Meta-models[M]. Advances in Global Optimization., 2015(1):251-261.
[16] ESTECO Inc. modeFRONTIER 2016[CP]. ESTECO Inc, Italy, 2016.
[17]赵选民.试验设计方法[M].北京：科学出版社, 2006.
[18]万伦，宋文武，符杰.隔舌安放角对中比转速离心泵非定常性能的影响[J].灌溉排水学报, 2018, 37(9):86-92.
[19]高红艳,魏占民.镫口扬水灌区输水干渠来沙特性解析[J].灌溉排水学报, 2018,37(7):99-105.
[20]陈雪丽,魏正英,马睿佳,等.灌溉输水管道沟槽减阻研究[J].灌溉排水学报, 2018, 37(3):90-95.
[21]高振军,李浩,刘建瑞,等.回流孔径对磁力驱动离心泵内部流动的影响分析[J].灌溉排水学报, 2017, 36(11):70-78.
[22] ANSYS Inc. ANSYS CFX, Release 17.0[CP]. ANSYS Inc, USA, 2017.