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首页> 外文期刊>Metallurgical and Materials Transactions, A. Physical Metallurgy and Materials Science >Matrix-Erosion Tessellation: Comparing Particle Clustering Measures Extracted from Three-Dimensional vs Two-Dimensional Images
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Matrix-Erosion Tessellation: Comparing Particle Clustering Measures Extracted from Three-Dimensional vs Two-Dimensional Images

机译：矩阵侵蚀镶嵌：比较从三维图像和二维图像中提取的粒子聚类度量

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摘要

Microvoids can nucleate from second-phase particles, grow, coalesce, and ultimately result in ductile failure. Since the rate of nucleation has been shown to be greatly increased by the clustering of second-phase particles, it is important to be able to characterize the particle distribution within an engineering alloy. Recent technological advances have made it possible to obtain three-dimensional (3-D) images of microstructural particle fields, but traditional two-dimensional (2-D) imaging of metallographic samples remains more convenient and cost-effective. Therefore, the extent to which the true nature of 3-D clustering can be quantified using only 2-D images is of genuine interest. In this study, matrix-erosion tessellation and dilational counting techniques are extended from 2-D to 3-D in order to measure the spatial distribution characteristics of various virtual 3-D particle fields. The effects of image resolution are first investigated and a minimum resolution parameter is proposed. Individual 2-D planes are then extracted from the 3-D virtual images for analysis and comparison with the 3-D results. The minimum number of features for the 2-D image to be representative of the 3-D system is then assessed. It was found that the use of 2-D images is appropriate for identifying the general distribution type (i.e., ordered, random, or clustered) and for comparing the relative amounts of clustering. The 2-D-based measures are also able to detect the presence of stringers in materials with a preferred cluster orientation (e.g., rolled sheet).
机译：微孔可从第二相颗粒中成核，生长，聚结并最终导致延性破坏。由于已经显示出通过第二相颗粒的聚集，成核速率大大提高，因此重要的是能够表征工程合金中的颗粒分布。最近的技术进步使得获得微观结构粒子场的三维（3-D）图像成为可能，但是传统的金相样品二维（2-D）成像仍然更加方便且具有成本效益。因此，仅使用2-D图像可以量化3-D聚类的真实性质的程度就引起了人们的真正兴趣。在这项研究中，为了测量各种虚拟3-D粒子场的空间分布特征，将矩阵侵蚀细分和膨胀计数技术从2-D扩展到3-D。首先研究图像分辨率的影响，并提出最小分辨率参数。然后从3-D虚拟图像中提取单个2-D平面，以进行分析并与3-D结果进行比较。然后，评估代表3D系统的2D图像的最小特征数量。发现2-D图像的使用适合于识别总体分布类型（即，有序的，随机的或聚类的）以及用于比较聚类的相对量。基于2-D的度量还能够检测具有首选簇方向的材料（例如，卷材）中纵梁的存在。

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