不可压缩流体在涡流管中流动的结构参数优化算法及求解

Optimization Algorithm and Solution for Structural Parameters of Incompressible Fluid Flow in Vortex Tubes

文章针对不可压缩流体在管道中的扰流特性,通过数值求解找到了非等径垂直孔的最佳结构尺寸。利用通孔两侧直径尺寸的样本参数和一定范围内入射流体的基本参数作为决策变量,流体在X轴的最大位移作为因变量。该研究不考虑涡流管入口方向和位置的变化,采用控制参数的办法,形成必要的强制流发生。结果表明,PSO-BP神经网络模型的性能最好,R2等于0.99831。然而,使用文献中实验的参数范围,流体偏移的最大距离达到了1.844毫米,无法达到涡流启动的最佳位置。仿真结果显示,其r2比率在1.5倍以上,流体才能达到最佳偏移距离。

In this paper,the optimal structural size of non-equal diameter vertical hole is found by numerical solution in view of the turbulence characteristic of incompressible fluid in pipeline.The sample parameters of diameter sizes on both sides of the through-hole and basic parameters of incident fluid within a certain range are used as decision variables,and the maximum displacement of fluid on the X-axis is used as dependent variable.The change of the direction and position of the inlet of the vortex tube is not considered in this research,and the method of controlling parameters is used to form the necessary forced flow.The results show that the performance of PSO-BP neural network model is the best,R2 is equal to 0.99831.However,it uses the experimental parameter range in the literature,and the maximum distance of the fluid migration reaches 1.844 mm,which is unable to reach the optimal position of vortex start.The simulation results show that only when the r2 ratio is more than 1.5 times can the fluid achieve the optimal migration distance.