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首页> 外文期刊>Structural and multidisciplinary optimization >CFD simulation and Pareto-based multi-objective shape optimization of the centrifugal pump inducer applying GMDH neural network, modified NSGA-II, and TOPSIS
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CFD simulation and Pareto-based multi-objective shape optimization of the centrifugal pump inducer applying GMDH neural network, modified NSGA-II, and TOPSIS

机译：CFD仿真和基于帕累托的多目标形状优化，应用GMDH神经网络，改装NSGA-II和TOPSIS

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摘要

Inducer is an important device which is mounted upstream of the inlet to the main impeller of the centrifugal pump and rotates at the same rotational speed as the impeller. The main purpose of the inducer is to improve the suction performance of the pump, but this improvement is dependent on the geometrical parameters of the inducer. Therefore, it is essential to optimize these parameters. In the present study, the performance of an inducer is optimized by considering the inlet tip blade angle, the outlet tip blade angle, and the ratio of the outlet hub radius to inlet hub radius as design variables and the head coefficient, the hydraulic efficiency, and the required net positive suction head (NPSHR) as objective functions. The inducer performance is simulated using 3-D computational fluid dynamics (CFD) and compared with experimental data, which shows the validity of the used method and assumptions. Then the group method of data handling (GMDH) algorithm is used to model the objective functions with respect to design variables. Using the modified non-dominated sorting genetic algorithm II (NSGA-II) approach, Pareto fronts are then plotted and trade-off optimum points are obtained using the technique for order of preference by similarity to ideal solution (TOPSIS). Using multi-objective optimization, the head coefficient, the hydraulic efficiency, and NPSHR are improved 14.3%, 0.3%, and 30.2%, respectively. Recommended design points unveil significant optimum design principles that can be obtained only by using a multi-objective optimization approach.
机译：诱导器是一个重要的装置，其安装在进气口的上游，其在离心泵的主叶轮上，并以与叶轮相同的转速旋转。诱导剂的主要目的是提高泵的抽吸性能，但这种改进取决于诱导剂的几何参数。因此，必须优化这些参数。在本研究中，通过考虑入口尖端叶片角度，出口尖端叶片角度，出口枢纽半径与入口毂半径的比率和头部系数，液压效率，所需的净正抽头（NPSHR）作为客观功能。使用3-D计算流体动力学（CFD）模拟诱导物性能，并与实验数据进行比较，这表明使用了使用的方法和假设的有效性。然后，数据处理（GMDH）算法的组方法用于模拟关于设计变量的目标函数。使用修改的非主导分类遗传算法II（NSGA-II）方法，然后绘制帕累托前线，并使用该技术获得权衡最佳点，以便通过与理想的解决方案（TOPSIS）相似的优先顺序获得。使用多目标优化，头部系数，液压效率和NPSHR分别提高14.3％，0.3％和30.2％。推荐的设计点公布了通过使用多目标优化方法可以获得的显着最佳设计原则。

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