Microstructural banding is explored in 2D and 3D using serial sectioned micrographs. The banding is quantified using two parameters called the Band Continuity Index Cb and the Perpendicular Continuity Index Cp. The indexes determined from the 2D micrographs is shown to be sufficient for estimating the distribution of the bands in 3D. A stereological model employing oriented circular cylinders is established to represent the bands in steel microstructures. This model assumes that cylinders are distributed randomly inside of a box with their symmetry axes oriented in the same direction. The box is then cut parallel to the symmetry axes and rectangles are observed on the cut plane. The inverse relationship between the rectangles and the cylind...
Dual phase steels are well suited to the automotive application. Their microstru...
In material testing process, the assessment of 3D geometry from 2D microstructure images of material...
Data analysis in materials science is of increased interest due to the rate at which large datasets ...
Kernel estimators are proposed for estimating the cumulative distribution functions and the probabil...
The principle concern of the material scientist is the connection between microstructure, properties...
The continuous development of steel products requires the detailed investigation of relationships be...
In common metallographic laboratory practice, object distributions in discontinuous multi-phase micr...
Microstructural characterization of metallic materials is of paramount importance in the qualificati...
Quantification of mesoscale microstructures of polycrystalline materials is important for a range of...
International audienceIn the area of tessellation models, there is an intense activity to fully unde...
In the area of tessellation models, there is an intense activity to fully understand the classical m...
In sheet metal applications, the plastic anisotropy behavior of metallic materials is significantly ...
A novel method for the stereological assessment of arrays of directionally solidified dendrites is p...
In the recent years, dual phase steel sheets have been used extensively in automotive industry in or...
The stereological method for studying grain structures is presented, it determines the interrelation...
Dual phase steels are well suited to the automotive application. Their microstru...
In material testing process, the assessment of 3D geometry from 2D microstructure images of material...
Data analysis in materials science is of increased interest due to the rate at which large datasets ...
Kernel estimators are proposed for estimating the cumulative distribution functions and the probabil...
The principle concern of the material scientist is the connection between microstructure, properties...
The continuous development of steel products requires the detailed investigation of relationships be...
In common metallographic laboratory practice, object distributions in discontinuous multi-phase micr...
Microstructural characterization of metallic materials is of paramount importance in the qualificati...
Quantification of mesoscale microstructures of polycrystalline materials is important for a range of...
International audienceIn the area of tessellation models, there is an intense activity to fully unde...
In the area of tessellation models, there is an intense activity to fully understand the classical m...
In sheet metal applications, the plastic anisotropy behavior of metallic materials is significantly ...
A novel method for the stereological assessment of arrays of directionally solidified dendrites is p...
In the recent years, dual phase steel sheets have been used extensively in automotive industry in or...
The stereological method for studying grain structures is presented, it determines the interrelation...
Dual phase steels are well suited to the automotive application. Their microstru...
In material testing process, the assessment of 3D geometry from 2D microstructure images of material...
Data analysis in materials science is of increased interest due to the rate at which large datasets ...