Zairyo-to-Kankyo
Online ISSN : 1881-9664
Print ISSN : 0917-0480
ISSN-L : 0917-0480
Volume 69 , Issue 3
Showing 1-5 articles out of 5 articles from the selected issue
Commentary
Conference Publication
  • Koya Tokutake, Shinji Okazaki, Shohei Sasaki
    2020 Volume 69 Issue 3 Pages 66-72
    Published: March 10, 2020
    Released: September 02, 2020
    JOURNALS RESTRICTED ACCESS

    To investigating the long-term degradation of a heavy-duty coating, Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy along the depth direction of a vinyl ester resin organic coating containing glass flakes was conducted. The organic coating sample was applied to the inner surface of the bottom plate of the oil storage tank, and used for approximately seventeen years. In addition, the degradation evaluation using the electrical equivalent circuit (EEC) model considering depth direction distribution of R//C time-constant (Voigt measurement model) was examined in detail.

    In the FT-IR along the coating depth direction, no clear peak shift and/or disappearance of the spectrum was observed. On the other hand, the baseline of the Raman shift of the coating gradually increased from near the steel substrate interface toward coating surface. These results suggest that the long-term coating degradation appears as a difference in physical change along the depth direction, and supports the result that the impedance characteristics of the coating can be well-analyzed by Voigt measurement model. Furthermore, it is expected that the DC resistance value can be estimated accurately by the EEC analysis using Voigt measurement model.

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  • Takahiro Ozawa, Shintaro Yamamoto, Takuya Mori, Mitsutoshi Yokomizo, L ...
    2020 Volume 69 Issue 3 Pages 73-76
    Published: March 10, 2020
    Released: September 02, 2020
    JOURNALS RESTRICTED ACCESS

    The rust layer changing behavior of initial corrosion on carbon steel was investigated by XAFS analysis using the large synchrotron radiation. Analysis of XANES spectrum and RDF by machine learning showed that the change in valence state and Fe-O covalent bond distance corresponded well with the initial corrosion rate. The distribution of valence and Fe-O bond distance of corrosion products on the steel surface showed a different tendency. These results suggest that the combination of synchrotron radiation analysis and machine learning is effective for elucidating rust formation mechanisms in initial corrosion.

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  • Hina Sato, Makoto Nagasawa, Michio Kaneko, Hiroshi Iki
    2020 Volume 69 Issue 3 Pages 77-82
    Published: March 10, 2020
    Released: September 02, 2020
    JOURNALS RESTRICTED ACCESS

    Protective rust formed on Cr-Cu-Ni-P and Cr-Cu weathering steels (WSs) exposed for 44 years were analyzed to compare with previous studies for exposure test results for weathering steels. The formation of a typical protective rust composed of a polarizing layer (crystalline α-FeOOH and γ-FeOOH) and an insulation layer (fine α-FeOOH) was observed on both the weathering steels. Alloy elements were distributed in the protective rust layer. Cr enrichment was observed in the insulation layer. It was similar to previous studies and indicated that Cr contributed to form fine rust. Cu was present in the insulation layer, P was present in the insulation layer and the top of the polarizing layer, and Ni was present in the entire rust layer. Structure of the rust layers and the distribution of Cr and Ni were consistent in the results of previous studies, the exposure tests for less than 32 years, however there was a difference in the distribution of Cu and P.

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