首页> 外文期刊>International journal of multiscale computational engineering >IDENTIFYING MATERIAL PARAMETERS FOR A MICRO-POLAR PLASTICITY MODEL VIA X-RAY MICRO-COMPUTED TOMOGRAPHIC (CT) IMAGES: LESSONS LEARNED FROM THE CURVE-FITTING EXERCISES
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IDENTIFYING MATERIAL PARAMETERS FOR A MICRO-POLAR PLASTICITY MODEL VIA X-RAY MICRO-COMPUTED TOMOGRAPHIC (CT) IMAGES: LESSONS LEARNED FROM THE CURVE-FITTING EXERCISES

机译:通过X射线微计算机断层扫描(CT)图像识别微极塑性模型的材料参数:从曲线拟合练习中学习的经验教训

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Unlike a conventional first-order continuum model, the material parameters of which can be identified via an inverse problem conducted at material point that exhibits homogeneous deformation, a higher-order continuum model requires information from the derivative of the deformation gradient. This study concerns an integrated experimental-numerical procedure designed to identify material parameters for higher-order continuum models. Using a combination of micro-CT images and macroscopic stress-strain curves as the database, we construct a new finite element inverse problem which identifies the optimal value of material parameters that matches both the macroscopic constitutive responses and the meso-scale micropolar kinematics. Our results indicate that the optimal characteristic length predicted by the constrained optimization procedure is highly sensitive to the types and weights of constraints used to define the objective function of the inverse problems. This sensitivity may in return affect the resultant failure modes (localized vs. diffuse), and the coupled stress responses. This result signals that using the mean grain diameter alone to calibrate the characteristic length may not be sufficient to yield reliable forward predictions.
机译:与传统的一阶连续谱模型不同,传统的一阶连续谱模型可以通过在表现出均匀变形的材料点进行反演来识别其材料参数,而高阶连续谱模型则需要来自变形梯度导数的信息。这项研究涉及设计用于识别高阶连续模型的材料参数的集成实验数字程序。使用微CT图像和宏观应力-应变曲线的组合作为数据库,我们构造了一个新的有限元反问题,该问题确定了与宏观本构响应和中尺度微极运动学都匹配的材料参数的最佳值。我们的结果表明,由约束优化程序预测的最优特征长度对用于定义反问题目标函数的约束类型和权重高度敏感。这种敏感性反过来可能会影响最终的失效模式(局部与弥散)以及耦合的应力响应。该结果表明,仅使用平均粒径来校准特征长度可能不足以产生可靠的正向预测。

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