基于机器学习的高速复杂流场流动控制效果预测分析

Predictive analysis of flow control in high-speed complex flow field based on machine learning

流动控制激励器是主动流动控制技术的核心,其设计水平和工作性能直接决定了主动流动控制的应用效果和应用方向。为了获得流动控制激励器的作用规律,需要大量实验研究激励参数对控制效果参数的影响,实验代价较大。利用逆向等离子体合成射流激波控制实验数据,采用机器学习中的高斯过程回归模型,获得激励器参数(头锥直径、腔体体积、放电电容、出口直径)到控制效果参数(最大脱体距离)的映射规律,对比多种核函数下高斯过程回归的预测效果,采用特征重要性分析方法分析激励器参数对控制效果参数的影响程度。结果表明:对于小样本问题,采用2次多项式核函数Poly2的高斯过程回归预测精度最高。在特征重要性分析上,头锥直径对最大脱体距离的影响程度最大;其次是放电电容和腔体体积,2个参数的影响相近;出口直径影响最小。本文工作可为高速复杂流场流动控制实验中激励器各项参数的设置提供一定参考。

The flow control actuator is the core of the active flow control technology. The design level and performance of actuator directly determine the application direction and effect of active flow control. In order to obtain the action law of the flow control actuator, a large number of experiments are needed to study the influence of excitation parameters on control effect parameters, and the experimental cost is large. In this paper, the experimental data of jet shock control in reverse plasma synthesis are used, and the Gaussian process regression model in machine learning is used to obtain the mapping law from the actuator parameters(head cone diameter, cavity volume, discharge capacitance and outlet diameter) to the control effect parameters(maximum out of body distance). We compare the prediction effects of Gaussian process regression under various kernel functions, and analyze the influence of actuator parameters on control effect parameters by using the characteristic importance analysis method.The results show that for this small sample problem, Gaussian process regression with the quadratic polynomial kernel function Poly2 obtains the highest accuracy;in characteristic importance analysis, the head cone diameter has the greatest influence on the maximum separation distance, followed by discharge capacitance and cavity volume. The influence of these two parameters is similar, and the influence of the outlet diameter is the least. The work of this paper can provide some guidance for the setting of various parameters of the actuator in the flow control experiment of the high-speed complex flow field.