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作 者:周润 唐亮 李平 黄叙辉 Zhou Run;Tang Liang;Li Ping;Huang Xuhui(High Speed Aerodynamics Institute,China Aerodynamics Research and Development Center,Mianyang 621000,Sichuan,China)
机构地区:[1]中国空气动力研究与发展中心高速空气动力研究所,四川绵阳621000
出 处:《光学学报》2022年第9期31-38,共8页Acta Optica Sinica
基 金:国家自然科学基金(11472297)。
摘 要:由穿过扰动流场的光线偏折角测值重建流场密度,对深入认识复杂流动现象具有重要的意义。在由风洞视频测量方法得到穿过扰动流场光线偏折角的基础上,开展了复杂流动密度重建方法的研究。根据密度与折射率、光线偏折角的关系,运用变分法推导了带有先验信息的密度偏微分方程;通过人工神经网络对测量数据进行建模,有效抑制了由局部峰值丢失带来的误差放大问题。数值仿真和风洞实验结果表明,本文方法所得的密度重建结果明显优于直接求偏导数方法,尤其是在峰值处,本法方法在量值上具有更高的精准度,为复杂流动结构的定量分析提供了新途径。The reconstruction of flow field density from the measured value of light deflection angle passing through the disturbed flow field,it is great significance for the in-depth understanding of complex flow phenomena.Based on the deflection angle of light passing through the disturbed flow field obtained by the wind tunnel video measurement method,the reconstruction method of complex flow density is studied.According to the relationship among density,refractive index,and light deflection angle,the partial differential equation of density with prior information is derived by variational method.The artificial neural network is used to model the measured data,and the error magnification caused by the loss of local peak value is effectively suppressed.The results of numerical simulation and wind tunnel experiments show that the density reconstruction result of this method is obviously better than that of the direct partial derivative method,especially at the peak,this method has higher accuracy in terms of value,which provides a new way for the quantitative analysis of complex flow structure.
分 类 号:V556.5[航空宇航科学与技术—人机与环境工程] V211.7
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