“…A program named DC-2D was developed based on a public domain software of ImageJ to distinguish clusters in 2D cross-sectional images, in which each pair of particles were considered to belong to one cluster when the intersurface distance between the two particles is less than the Feret's diameter of the smaller particle. The inter-surface distance between the two particles is given by 25,26) ....... Where, (Xa,Ya) and (Xb,Yb) are the central coordinates of particles a and b in the cross-sectional image; da and db are the Feret's diameters of particles a and b; ds is the inter-surface distance of particle a and b. Figure 8 shows examples of distinguished clusters in a cross-sectional image processed by the program of DC-2D.…”
Section: Quantitative Analysis Methods For Cluster Numbermentioning
Particle coagulation plays a key role in steel refining process to remove inclusions. Many research works focus on the behaviors of particle coagulation. To reveal its mechanism water model experiments have been performed by some researchers including the authors' group. In this paper, experiments of particle coagulation were carried out with molten Al including SiC particles in a mechanically agitated crucible with two baffles. Particle coagulation and formation of clusters were observed on the microscopy images of as-polished samples. Three-dimensional (3D) analysis of the clusters in solidified Al was implemented by X-ray micro CT available at SPring-8. The methods to distinguish clusters on two-dimensional (2D) cross-sectional images were discussed, which were established in the previous works by the present authors' group. The characteristics of the 3D SiC clusters and their 2D cross-sections were analyzed. The statistical ranges of the parameters for 2D clusters were used as criterions to distinguish the clusters on 2D microscopy images from the as-polished samples. The kinetics of SiC particle coagulation was studied by the measured cluster number density and size using our program to distinguish cluster in 2D crosssectional images according to 3D information (DC-2D-3D). The calculated and experimental results of the SiC particle coagulation in molten Al agree well with each other.
“…A program named DC-2D was developed based on a public domain software of ImageJ to distinguish clusters in 2D cross-sectional images, in which each pair of particles were considered to belong to one cluster when the intersurface distance between the two particles is less than the Feret's diameter of the smaller particle. The inter-surface distance between the two particles is given by 25,26) ....... Where, (Xa,Ya) and (Xb,Yb) are the central coordinates of particles a and b in the cross-sectional image; da and db are the Feret's diameters of particles a and b; ds is the inter-surface distance of particle a and b. Figure 8 shows examples of distinguished clusters in a cross-sectional image processed by the program of DC-2D.…”
Section: Quantitative Analysis Methods For Cluster Numbermentioning
Particle coagulation plays a key role in steel refining process to remove inclusions. Many research works focus on the behaviors of particle coagulation. To reveal its mechanism water model experiments have been performed by some researchers including the authors' group. In this paper, experiments of particle coagulation were carried out with molten Al including SiC particles in a mechanically agitated crucible with two baffles. Particle coagulation and formation of clusters were observed on the microscopy images of as-polished samples. Three-dimensional (3D) analysis of the clusters in solidified Al was implemented by X-ray micro CT available at SPring-8. The methods to distinguish clusters on two-dimensional (2D) cross-sectional images were discussed, which were established in the previous works by the present authors' group. The characteristics of the 3D SiC clusters and their 2D cross-sections were analyzed. The statistical ranges of the parameters for 2D clusters were used as criterions to distinguish the clusters on 2D microscopy images from the as-polished samples. The kinetics of SiC particle coagulation was studied by the measured cluster number density and size using our program to distinguish cluster in 2D crosssectional images according to 3D information (DC-2D-3D). The calculated and experimental results of the SiC particle coagulation in molten Al agree well with each other.
“…The cleanliness steel is a relative concept which has been greatly improved by the progress of steel refining techniques and equipment employing inclusion coagulation and bubble flotation. [4][5][6][7][8][9] To evaluate the steel refining techniques, it is critical to estimate the number density and the size distribution of the inclusion is steel samples.…”
In this paper, we investigate the reliability of estimating of inclusion size distribution and number density in steel by using stereological methods. The magnitude of the inclusion concentration in steel is evaluated by the total oxygen and the assumed average inclusion sizes. The principles of Schwartz-Saltykov (SS) and modified SS (MSS) methods are introduced. A simulation model is developed to disperse particles with a predefined particle size distribution (PSD) randomly into a three dimensional (3D) space. A series of test planes are generate to measure the two dimensional (2D) PSD and particle number density (PND) on the cross-sections (CS). The SS and MSS methods are applied to investigate the reliability of the translation between the 3D and 2D information of the system, such as the 2D and 3D PSD and PND. The influence of predefined 3D PSD on the reliability of the stereological methods are studied, such as mono sized, lognormal and normal distributions. The effect of the representative group diameters in the discretized groups for SS and MSS methods is investigated as well.
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