SummaryA three-dimensional (3D) internal structure observation system based on serial sectioning was developed from an ultrasonic elliptical vibration cutting device and an optical microscope combined with a high-precision positioning device. For bearing steel samples, the cutting device created mirrored surfaces suitable for optical metallography, even for long-cutting distances during serial sectioning of these ferrous materials. Serial sectioning progressed automatically by means of numerical control. The system was used to observe inclusions in steel materials on a scale of several tens of micrometers. Three specimens containing inclusions were prepared from bearing steels. These inclusions could be detected as two-dimensional (2D) sectional images with resolution better than 1 μm. A three-dimensional (3D) model of each inclusion was reconstructed from the 2D serial images. The microscopic 3D models had sharp edges and complicated surfaces.

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When thermosetting resin changes from liquid to solid in cure process, the elasticity and volume also vary with the degree of reaction based on the tempearture history. Therefore, the accurate predictive model for the degree of reaction is necessary to set the appropriate temperature condition. Since the reaction model with multiple reaction peaks must consider the relationship of each reaction peak, it cannot be expressed only by single-reaction models proposed in the many previous studies. In this study, the reaction behavior for thermosetting resins with two reaction peaks was modeled by the reaction rate and ratio of total heat for each reaction peak. In addition, the diffusion control model for reaction which represents the decrease of the reaction rate by vitrification was applied to the reaction rate term for the second reaction peak. Furthermore, the temperature dependence of the diffusion control model was incorporated. The calculation results using the diffusion control model were agreed with nonisothermal differential scanning calorimetry (DSC) measurement data than Kamal model commonly used with or without temperature dependence. On the other hand, for isothermal measurement data, the temperature dependence diffusion control model was able to predict degree of reaction accurately at a temperature lower than the glass transition temperature.

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