Fracture surfaces of X70 steel DWTT broken samples are analysed using new surface evaluation concept. The presented approach is an alternative to an expert determining a ratio between the ductile and brittle fracture area. The analysed data source, i.e. , and coordinates of points of fracture surface, comes from 3D scan using Limess Measurement Technique. Beside formerly used fractal geometry approach, new concept based on normal vector characteristics is used. The fracture surface net is generated by triangulation of points of fracture surface. For every triangle, the normal vector is computed. Thereafter, normal vector characteristics are clustered via k-means++ clustering algorithm. Application of the algorithm improves the correct detection of the brittle and ductile fractures significantly, so that the achieved clusters highly correspond to the real distribution of the ductile and brittle fracture areas on DWTT surface. Furthermore, applied methods are computationally very fast, so that it is possible to apply them for the scans with considerably higher magnitude. The correctness of the final cluster results are evaluated comparing with the real displacement of the brittle and ductile fracture, and by using various theoretical approaches.Keywords: DWTT samples, ductile and brittle fracture, k-means clustering.
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