基于光流算法的粒子图像测速技术研究和验证

光流测量技术作为一种新的空气动力学实验技术,以其像素级分辨率的矢量场测量优势获得广泛的应用。光流测量技术使用光流约束方程,配合平滑限定条件,可以进行速度场测量,获得高分辨率的全局矢量场。本文首先通过研究积分最小化光流测速理论和算法,采用C++编写光流速度测量程序;然后通过三种典型的人工位移图像对光流计算程序进行了验证,并将结果和标准位移分布进行比对分析,以指导如何在实际应用中获得高精度光流速度场;最后进行小型风洞后向台阶实验,利用高速相机拍摄示踪粒子图像,使用光流计算程序获得速度矢量场,同采用互相关算法的粒子图像测速计算结果相比较,体现出光流计算方法像素级分辨率的矢量场测量优势。     

Mechanical quadrature methods and extrapolation for solving nonlinear boundary Helmholtz integral equations

This paper presents mechanical quadrature methods (MQMs) for solving nonlinear boundary Helmholtz integral equations. The methods have high accuracy of order O(h ³) and low computation complexity. Moreover, the mechanical quadrature methods are simple without computing any singular integration. A nonlinear system is constructed by discretizing the nonlinear boundary integral equations. The stability and convergence of the system are proved based on an asymptotical compact theory and the Stepleman theorem. Using the h ³-Richardson extrapolation algorithms (EAs), the accuracy to the order of O(h ⁵) is improved. To slove the nonlinear system, the Newton iteration is discussed extensively by using the Ostrowski fixed point theorem. The efficiency of the algorithms is illustrated by numerical examples.     

机械求积法及其外推算法求解Helmholtz非线性边界积分方程

当Helmholtz微分方程转化为非线性边界积分方程后,可以利用机械求积法求得近似解,此方法具有较高的收敛精度阶O(h3)和较低的计算复杂度.构造机械求积法时,一个非线性方程系统通过离散非线性积分方程得到.此外,每个矩阵元素的值都不需要计算任何奇异积分.根据渐近紧理论和Stepleman定理,整个系统的稳定性和收敛性得到了证明.利用h3-Richardson外推算法,收敛精度阶可以提高到O(h5).为了求解非线性方程组,利用Ostrowski不动点定理研究了Newton的解的收敛性.几个算例从数值上说明了本算法的有效性.     

High accuracy eigensolution and its extrapolation for potential equations

From the potential theorem, the fundamental boundary eigenproblems can be converted into boundary integral equations （BIEs） with the logarithmic singularity. In this paper, mechanical quadrature methods （MQMs） are presented to obtain the eigensolutions that are used to solve Laplace＇s equations. The MQMs possess high accuracy and low computation complexity. The convergence and the stability are proved based on Anselone＇s collective and asymptotical compact theory. An asymptotic expansion with odd powers of the errors is presented. By the h3-Richardson extrapolation algorithm （EA）, the accuracy order of the approximation can be greatly improved, and an a posteriori error estimate can be obtained as the self-adaptive algorithms. The efficiency of the algorithm is illustrated by examples.     

高精度特征解及其外推求解位势方程

根据位势理论,基本边界特征值问题可转化为具有对数奇性的边界积分方程.利用机械求积方法求解特征值和特征向量,以及利用这些特征解求解Laplace方程.特征解和Laplace方程的解具有高精度和低的计算复杂度.利用Anselone聚紧和渐近紧理论,证明了方法的收敛性和稳定性.此外,还给出了误差的奇数阶渐近展开.利用h3-Richardson外推,不仅误差近似的精度阶大为提高,而且,得到的后验误差估计可以构造自适应算法.具体的数值例子说明了算法的有效性.