论文标题
拉格朗日跟踪碰撞液滴
Lagrangian tracking of colliding droplets
论文作者
论文摘要
我们引入了一种新的Lagrangian粒子跟踪算法，该算法在三个维度上跟踪粒子到接近接触的轨迹之间的分离。该算法还检测到低韦伯数二进制碰撞，导致结合以及液滴破裂。通过查找描述每个身体边缘的圆圈集，在二维高分辨率数字图像中鉴定出粒子。这允许识别即使对于嘈杂的图像，并且不调用其他时间数据，即使在投影中重叠的粒子也将超过80％。该算法通过最大程度地减少惩罚函数来构建从三维粒子坐标的轨迹，该惩罚函数是使用四个时刻的信息加权与预期粒子坐标的加权总和。这种新的混合算法通过合成数据验证，发现比其他常用方法完美地重现了更多的轨迹。对于颗粒平均移动的颗粒的精度为95％，碰撞是碰撞的。
We introduce a new Lagrangian particle tracking algorithm that tracks particles in three dimensions to separations between trajectories approaching contact. The algorithm also detects low Weber number binary collisions that result in coalescence as well as droplet break-up. Particles are identified in two-dimensional high-resolution digital images by finding sets of circles to describe the edge of each body. This allows identification of particles that overlap in projection by over 80% even for noisy images and without invoking additional temporal data. The algorithm builds trajectories from three-dimensional particle coordinates by minimizing a penalty function that is a weighted sum of deviations from the expected particle coordinates using information from four moments in time. This new hybrid algorithm is validated against synthetic data and found to perfectly reproduce more trajectories than other commonly used methods. Collisions are detected with 95% accuracy for particles that move on average less than one tenth the distance to their nearest neighbor.
