HOME > Profile > KATAYAMA, Hideki
- Deputy Director, Research Center for Structural Materials
- Chief Researcher, Corrosion Research Group, Materials Evaluation Field, Research Center for Structural Materials
- Field Director, Materials Evaluation Field, Research Center for Structural Materials
- Extreme Environment Material Data Unit, Materials Data Platform, Advanced Engineering and Services Division
- Address
- 305-0047 1-2-1 Sengen Tsukuba Ibaraki JAPAN [Access]
External affiliations
- 東京理科大学 創域理工学部 先端化学科
- 法政大学 生命科学部 環境応用化学科
Research
- Keywords
材料加工・処理
PublicationsNIMS affiliated publications since 2004.
Research papers
- KATAYAMA, Hideki. IV. Electrochemical Measurements in Various Environments: Atmospheric Corrosion II (Electrochemical Impedance Method). CORROSION ENGINEERING. [7] (2018) 258-266 10.3103/s0892422818070030
- 片山英樹, 山本正弘. 大気腐食機構解明のための腐食速度のモニタリング法. 防錆管理. (2001)
- 片山 英樹. 腐食データシート. 金属. (2021) 300-305
Books
- 片山 英樹, 藤本慎司. ガルバニック腐食数値シミュレーション. 革新構造材料とマルチマテリアル 下 プロジェクト成果総覧. オーム社, 2023, 4.
- 片山 英樹. 屋外腐食試験の概要と試験データの活用. 金属材料の腐食防食技術大系. NTS, 2025, 10.
- 片山 英樹. 鋼構造物の部位レベルの腐食進行性と腐食環境の評価手法. 丸善, 2019
Proceedings
- 片山 英樹, 山田 茉耶, 星 芳直, 四反田 功, 板垣昌幸. 電気化学インピーダンス法によるモルタル中鉄筋の腐食モニタリング. コンクリート構造物の補修,補強,アップグレード論文報告集. (2018) 621-624
- 片山英樹. 電気化学的手法による塗膜下腐食の評価. 腐食防食部門委員会資料. (2009) 23-30
- KATAYAMA, Hideki, MIYAHARA Ryota, HOSHI Yoshinao, SHITANDA Isao, ITAGAKI Masayuki. Corrosion protection property of corrosion products of zinc galvanized steels. Proc of EUROCORR 2014. (2014)
Presentations
- KATAYAMA, Hideki. Corrosion protection property of corrosion products of zinc galvanized steels. EUROCORR 2014. 2014
- ONO, Yoshinori, WADA, Kentaro, TERADA, Hayato, FUKUDA, Mana, KOMATSU, Masayuki, YURI, Tetumi, UCHINO, Takashi, HAYAKAWA, Masao, KATAYAMA, Hideki, 日比 政昭, SHIMIZU, Tadashi. Development of a Materials Properties Evaluation Facility to Support Research and Development of Liquefied Hydrogen-Related Equipment. 30th International Cryogenic Engineering Conference and International Cryogenic Materials Conference 2026 (ICEC30/ICMC2026). 2026 Invited
- 片山 英樹. 鋼製構造材料の腐食劣化挙動解明における電気化学インピーダンス法の有効性. 電気化学会第93回大会. 2026 Invited
Misc
- 片山 英樹, 千葉 誠, 坂入 正敏, 伏見 公志, 菅原 優, 五十嵐 誉廣, 多田 英司, 星 芳直, 土谷 博昭, 押川 渡. インフラ劣化診断のためのデータサイエンス研究会の成果. ふぇらむ. 31 [6] (2026) 366-371
- 片山 英樹. 電気化学インピーダンス法を活用した構造材料の腐食モニタリング. 金属. 96 [6] (2026) 449-454
- 小野 嘉則, 和田 健太郎, 寺田 隼斗, 早川 正夫, 片山 英樹, 日比 政昭, 清水 禎. 液化水素関連機器の研究開発を支える材料特性評価と材料データベース基盤の構築へ向けて. 低温工学. 61 [4] (2026) 162-169 10.2221/jcsj.61.162 Open Access
Published patent applications
Society memberships
日本鉄鋼協会, 表面技術協会, 腐食防食学会, Electrochemical Society, 電気化学会, 金属学会, 原子力学会
Research Center for Structural Materials
Corrosion Risk Prediction for Steel Structures Using Hyperspectral Analysis
Hyperspectral imaging, Carbon steel, Atmospheric corrosion, Corrosion products, SAM analysis, Corrosion risk prediction
Overview
Preventive maintenance of steel structures requires techniques for assessing both their current corrosion condition and subsequent corrosion progression. In this study, corrosion products formed on carbon steel specimens exposed to ordinary and sheltered outdoor environments at Choshi, Chiba and Miyakojima, Okinawa for up to 2.5 years were identified using hyperspectral measurements and Spectral Angle Mapper (SAM) analysis. Reference spectra of α-FeOOH, β-FeOOH, γ-FeOOH, and Fe₃O₄ were used to evaluate their spatial distributions and surface fractions. Although the surface fractions of γ-FeOOH and Fe₃O₄ showed no correlation with the increase in corrosion loss, γ-FeOOH predominated under ordinary exposure, whereas Fe₃O₄ predominated under sheltered exposure, indicating that these products could help distinguish between exposure environments. In contrast, the surface fractions of α-FeOOH and β-FeOOH showed positive and negative correlations, respectively, with the increase in corrosion loss over the subsequent year. These findings demonstrate the potential of optical information from surface rust for corrosion risk assessment.
Novelty and originality
● Corrosion risk assessment based on rust identification
● Evaluation of the spatial distributions and surface fractions of different corrosion products using hyperspectral data
● Verification of applicability under different outdoor exposure conditions
● Identification of potential indicators of subsequent corrosion progression
Details
Carbon steel specimens exposed to ordinary and sheltered environments at Choshi, Chiba, and Miyakojima, Okinawa, for 1.5 years were examined using a hyperspectral camera. SAM analysis was used to visualize the spatial distributions of surface corrosion products. Reflectance spectra were acquired over a wavelength range of 400–1100 nm, and each corrosion product was identified by evaluating spectral similarity at 500 and 760 nm using reference spectra of four known corrosion products. In Fig. 1, α-FeOOH, β-FeOOH, γ-FeOOH, and Fe₃O₄ are represented by blue, yellow, red, and gray, respectively. At both sites, γ-FeOOH was predominantly detected under ordinary exposure, whereas Fe₃O₄ was predominantly detected under sheltered exposure, revealing differences in surface rust associated with the exposure environment. The detection of Fe₃O₄ suggests an association with prolonged wet conditions. The surface fraction of each corrosion product was calculated from the number of pixels assigned to its corresponding color, enabling evaluation of the distributions and fractions of corrosion products that are difficult to distinguish visually.
The surface fraction of each corrosion product was then compared with the increase in corrosion loss over the subsequent year (Figure 2). For example, the increase was calculated as the difference in corrosion loss between specimens exposed for 0.5 and 1.5 years. A one-year comparison interval was used to reduce seasonal effects. While no clear correlations were observed for γ-FeOOH or Fe₃O₄, the surface fraction of α-FeOOH showed a positive correlation with the increase in corrosion loss, whereas that of β-FeOOH showed a negative correlation. These results suggest that the surface fractions of α-FeOOH and β-FeOOH may serve as indicators of subsequent corrosion progression. Further work is needed to improve the identification accuracy of mixed rust and validate the quantitative assessment of surface fractions. Validation across a wider range of environments is also necessary to clarify the relationship between corrosion products and subsequent corrosion progression.
Summary
Hyperspectral measurements combined with SAM analysis enabled identification of corrosion products on carbon steel after outdoor exposure and evaluation of their spatial distributions and surface fractions. The surface fractions of α-FeOOH and β-FeOOH showed positive and negative correlations, respectively, with the increase in corrosion loss over the subsequent year. These findings demonstrate the potential of optical information from surface rust to support corrosion risk assessment and preventive maintenance of steel structures.



