Abstract A multi-modal data recombination method that enables the automated, quantitative and statistical assessment of strain localization as a function of the microstructure is presented. It consists of merging high resolution digital image correlation (HR-DIC) datasets collected in a scanning electron microscope (SEM), with crystallographic data obtained from electron back-scattered diffraction (EBSD). As the data is typically gathered over large areas (about 1 mm2), this method enables the quantitative assessment of plastic strain localization over hundreds to thousands of grains, yet with a spatial resolution of tens of nanometers. The data is treated in a hierarchical manner so that strain localization phenomena can be studied as a function of phases, texture and grain orientation. The use of discontinuity tolerant DIC codes, such as Heaviside DIC (H-DIC) in the present case, enables identification the active slip system associated with slip band discontinuities. Analyses conducted over thousands of bands in thousands of grains enable the quantitative assessment of fundamental plasticity laws. The capabilities of this method are shown through application to Ti-6Al-4V and Inconel 718 alloys.

中文翻译：

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通过多模态数据重组自动定量分析塑性应变定位

摘要 提出了一种多模态数据重组方法，可以自动、定量和统计地评估作为微观结构函数的应变定位。它包括合并在扫描电子显微镜 (SEM) 中收集的高分辨率数字图像相关 (HR-DIC) 数据集，以及从电子背散射衍射 (EBSD) 获得的晶体学数据。由于数据通常是在大面积（约 1 平方毫米）上收集的，因此该方法可以对数百至数千个晶粒的塑性应变定位进行定量评估，但空间分辨率为数十纳米。以分层方式处理数据，以便可以将应变局部化现象作为相、纹理和晶粒取向的函数进行研究。使用不连续容忍 DIC 代码，例如本案例中的 Heaviside DIC (H-DIC)，可以识别与滑带不连续性相关的主动滑移系统。对数千个晶粒中的数千条带进行分析，可以对基本塑性定律进行定量评估。这种方法的能力通过对 Ti-6Al-4V 和 Inconel 718 合金的应用来展示。