In this work, the sensitivity-based virtual fields have been applied to identify two anisotropic plasticity models (Hill48, Yld2000-2D) using a deep-notched tensile test performed on flat samples of cold-rolled sheet of DC04 steel. The material was characterised using the standard protocol to obtain the reference sets of parameters. Deformation data was obtained during deep-notched tests using stereo digital image correlation and the virtual fields method was employed to identify material parameters. It was found that the sensitivity-based virtual fields outperform the standard user-defined virtual fields in terms of accuracy.

中文翻译：

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用于识别各向异性塑性模型的基于灵敏度的虚拟场的实验验证

在这项工作中，基于灵敏度的虚拟场已被应用于识别两个各向异性塑性模型（Hill48，Yld2000-2D），使用深缺口拉伸试验对 DC04 钢冷轧板的扁平样品进行。使用标准方案表征材料以获得参考参数集。在使用立体数字图像相关性的深缺口测试期间获得变形数据，并采用虚拟场方法来识别材料参数。发现基于灵敏度的虚拟场在准确性方面优于标准的用户定义的虚拟场。