RESUMEN
The copper molten marks at a fire site provide important clues for determining the causes of fire. Four factors have been presented to quantitatively discriminate copper molten marks, namely the fraction of (001) component perpendicular to the demarcation line, the grain aspect ratio, the fraction of Σ3 boundaries, and the fraction of maximum grain size. However, only laboratory-level results of these parameters have been presented, and their applicability in actual fires is yet to be verified. In this study, a fire reproduction experimental system was configured to generate molten marks similar to those in actual fire sites. The molten marks were measured by electron backscatter diffraction and applied to the four discriminant factors. The results obtained similar characteristics to those of the laboratory unit, confirming the applicability of the four discriminant factors. Discriminant equations and processes that can distinguish the primary and secondary arc beads were derived using the molten marks generated in the laboratory and reproduction experiments. Furthermore, a probabilistic discrimination method and classification model developed by machine learning were proposed. Therefore, the use of the discriminants in actual fires can improve the reliability of the statistics and prevent the recurrence of similar fires.
RESUMEN
The microstructure of molten marks changes according to ambient temperatures, when a short circuit occurs. Investigation of microstructural changes is important for understanding the properties of copper and examining the cause of a fire. In this study, the boundary characteristics and grain-size distribution of molten marks-primary-arc beads (PABs), which short-circuited at room temperature (25 °C), and secondary-arc beads (SABs), which short-circuited at high temperatures (600 °C, 900 °C)-were compared using electron backscatter diffraction. The distribution of Σ3 boundaries was compared, and it was found that SABs have a higher fraction of Σ3 boundaries than PABs. Moreover, it was confirmed that the ratio of maximum grain size (area) to the total area of the molten mark in SABs is larger than that in PABs. Thus, reliable discriminant factors were suggested, such as the fraction of Σ3 boundaries and normalized maximum grain size, which can distinguish PABs and SABs. The four discriminant factors, such as the (001)//LD, GAR, fraction of Σ3 boundaries, and fraction of maximum grain size to the total molten-mark area, were verified using the machine learning of t-SNE and Pearson correlation analyses.
