A methodology to adapt optical deformation analysis in material characterization and model validation

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Optical deformation analysis has become a core part of materials characterization and model validation. In the field of engineering, this development is supported by achievements in the field of digital image correlation, in addition to constant progress in optical sensors and computer hardware. When using digital image correlation in practice, however, there are still critical challenges, especially for three-dimensional measurement tasks, such as the (user-independent) selection of suitable initial values and adapted evaluation parameters in the algorithm, the meaningful calculation of the evaluation variables (usually strains) and their spatio-temporal derivations, the inclusion of environmental influences or dealing with discontinuities. In abstract form, these existing challenges can be explained by the fact that optical deformation analysis is a mathematically ill-posed problem. On the one hand, this concerns the task of tracking the motion of material points over time and, in the case of stereo or multi-camera systems, the spatial reconstruction of the measurement object. The mathematically ill problem is countered by the introduction of assumptions and boundary conditions, which in a certain respect can also be understood as modeling of the measurement task, by approaches of data assimilation and regularization. In the research project applied for, these approaches are taken up, designed and researched against the background of material characterization and testing. Assumptions and boundary conditions for solving the mathematically ill-posed problem should not only be adaptable to the measurement task at hand, but also take into account the further use of the recorded information, especially for parameter identification and model validation. The aim of the intended research project is, starting from the theoretical foundation of the field of computer vision, to understand the coupled connections between optical detection, evaluation approach and modeling context, on the one hand in a virtual environment of this overall system and on the other hand in a real experiment.