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Abstract：
Material models are required to solve continuum mechanical problems. These models contain parameters that are usually determined by application-specific test setups. In general, the theoretically developed models and, thus, the parameters to be determined become increasingly complex, e.g., incorporating higher-order motion derivatives, such as the strain or strain rate. Therefore, the strain rate behaviour needs to be extracted from experimental data. Using image data, the most-common way in solid experimental mechanics to do so is digital image correlation. Alternatively, optical flow methods, which allow an adaption to the underlying motion estimation problem, can be applied. In order to robustly estimate the strain rate fields, an optical flow approach implementing higher-order spatial and trajectorial regularisation is proposed. Compared to using a purely spatial variational approach of higher order, the proposed approach is capable of calculating more accurate displacement and strain rate fields. The procedure is finally demonstrated on experimental data of a shear cutting experiment, which exhibited complex deformation patterns under difficult optical conditions.
摘要：
需要材料模型来解决连续机械问题。这些模型包含通常由特定于应用程序的测试设置确定的参数。总的来说,理论上开发的模型，因此，要确定的参数变得越来越复杂，例如，结合高阶运动导数，如应变或应变率。因此,应变率行为需要从实验数据中提取。使用图像数据，在固体实验力学中最常见的方法是数字图像相关。或者，光流法，这允许适应潜在的运动估计问题，可以应用。为了稳健地估计应变率场，提出了一种实现高阶空间和轨迹正则化的光流方法。与使用高阶的纯空间变分方法相比，所提出的方法能够计算更精确的位移和应变率场。最后在剪切实验的实验数据上证明了该程序，在困难的光学条件下表现出复杂的变形模式。
