Finite element stereo digital image correlation (FE-SDIC) requires a crucial calibration phase in which the initial CAD needs to be updated to fit the actual shape of the specimen. On the one hand, the use of a FE mesh facilitates the coupling of measurements with simulation tools. On the other hand, it provides a unique, fine description of both the geometry and the displacement, which often makes the shape measurement problem highly ill-posed. As a remedy, we propose a hybrid isogeometric-FE strategy that can measure a shape in terms of spline functions while considering as an input and output the analysis-suitable FE mesh. Making use of the appealing spline refinement procedures and of Bezier-based operators, multilevel smooth spline dis-cretizations are built concurrently with the initial FE subspace and related to the multi-scale images used for the initialization of the shape measurement. It results in a geometrically sound regularization which provides a spline parametrization of the optimal shape along with its FE twin. A non-invasive implementation from an existing FE-SDIC code is also detailed. The performance of the proposed method is assessed on real images and comparisons are made with other published techniques to prove its efficiency.

中文翻译：

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基于网格的 3D 形状测量的无创多级几何正则化

有限元立体数字图像相关 (FE-SDIC) 需要一个关键的校准阶段，在该阶段需要更新初始 CAD 以适应样本的实际形状。一方面，有限元网格的使用促进了测量与仿真工具的耦合。另一方面，它提供了对几何形状和位移的独特、精细的描述，这通常使形状测量问题非常不适定。作为补救措施，我们提出了一种混合等几何有限元策略，该策略可以根据样条函数测量形状，同时将适合分析的有限元网格视为输入和输出。利用吸引人的样条细化程序和基于贝塞尔的算子，多级平滑样条离散化与初始 FE 子空间同时构建，并与用于形状测量初始化的多尺度图像相关。它导致几何合理的正则化，提供最佳形状的样条参数化及其有限元孪生。还详细介绍了现有 FE-SDIC 代码的非侵入性实施。所提出方法的性能在真实图像上进行评估，并与其他已发表的技术进行比较以证明其效率。