Applicable scope of estimation of three-dimensional particle size distribution by the Goldsmith-Cruz-Orive and improved methods
Applicable scope of estimation of three-dimensional particle size distribution by the Goldsmith-Cruz-Orive and improved methods
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DOI：
10.1016/j.powtec.2022.117462
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发表时间：
2022-05
影响因子：
5.2
通讯作者：
T. Ueda
中科院分区：
文献类型：
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作者：
T. Ueda
当内部结构和/或内含物在给定领域中是感兴趣的时，通常在颗粒切片上进行显微镜观察，并且所讨论的颗粒包括例如砂、颗粒、细胞、空隙、晶体等组分。然而，在实践中，由于2D和3D观察之间的体视学差异，通过颗粒截面的二维（2D）观察确定的颗粒尺寸分布不同于实际的三维（3D）颗粒尺寸分布。在从2D尺寸分布估计3D的各种方法中，已知Goldsmith-Cruz-Orive方法（GCO）提供高估计精度。在这项研究中，GCO和一个新的改进的GCO方法（MGCO）进行了系统的研究，以确定其适用范围的尺寸分布范围，不寻常的形状（阶梯状）的尺寸分布，椭球颗粒的轴长比，和输入数据的错误。在这项研究的结果中，MGCO方法表现出更大的估计精度比GCO的大小分布的范围内，合理的估计精度的情况下，阶梯状的大小分布（而GCO没有），更大的鲁棒性比GCO相对于椭球体颗粒的轴长比，更敏感的输入数据错误比GCO。阐明了各种方法的适用范围，有利于GCO方法在各种颗粒物中的实际应用。
Microscopic observation is commonly performed on particle sections when the internal structure and/or inclusion is of interest in a given field, and the particles in question include sand, grain, cell, void, crystal, etc. components for example. However, in practice, the particle size distributions determined by two-dimensional (2D) observation of particle sections differ from the actual three-dimensional (3D) particle size distributions, due to the stereological difference between 2D and 3D observation. Among the various methods of estimating 3D from 2D size distributions, the Goldsmith-Cruz-Orive method (GCO) is known to provide high estimation accuracy. In this study, the GCO and a newly improved GCO method (MGCO) were systematically investigated to determine their applicable scope in terms of the range of size distributions, unusually-shaped (step-like) size distributions, the axis length ratio of ellipsoidal particles, and input data errors. Among the study's results, the MGCO method showed greater estimation accuracy than GCO irrespective of the range of size distributions, reasonable estimation accuracy in the case of step-like size distributions (while GCO did not), greater robustness than GCO with respect to the axis length ratio of ellipsoidal particles, and more sensitivity to input data errors than GCO. Elucidation of the applicable scopes of the respective methods facilitates the practical use of the GCO methods for various types of particles.