Estimation and risk assessment of rebar corrosion distribution inside RC using mesoscale analysis and AI image analysis

2021 Fiscal Year Final Research Report

• Project/Area Number: 19H02210
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 22010:Civil engineering material, execution and construction management-related
• Research Institution: The University of Tokyo
• Principal Investigator: Nagai Kohei 東京大学, 生産技術研究所, 准教授 (00451790)
• Co-Investigator(Kenkyū-buntansha): 酒井 雄也 東京大学, 生産技術研究所, 准教授 (40624531)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: コンクリート / 腐食 / 微細構造解析 / 内部推定

Outline of Final Research Achievements

We have developed a computational approach for estimating the distribution of corrosion along the length of a reinforcing bar from the observed surface crack widths. The approach is based on mesoscale simulations of reinforced concrete, using rigid-body-spring models (RBSM), guided by Model Predictive Control (MPC). It is extended to account for differing (smaller) crack openings, multiple instances of localized corrosion, and added confinement due to the presence of stirrups. Accuracy of the proposed approach is demonstrated through comparisons with laboratory tests of steel corrosion within concrete. The crack distribution observed on the concrete surface is automatically reproduced by optimized application of internal expansion within the mesoscale model, from which the corrosion distribution is estimated. The estimated corrosion distribution is accurate when compared to the measured corrosion of bars removed from the test specimens.

Free Research Field

土木工学

Academic Significance and Societal Importance of the Research Achievements

鉄筋コンクリート構造物の損傷において最も問題になるのは鉄筋の腐食であるが，損傷後の合理的な対策は容易ではない。その主たる原因はコンクリート表面から鉄筋の腐食状況が確認できないことである。内部の腐食の状況が確認できれば，その腐食程度に応じて耐力等の構造性能を推定することができ，対策の要否や方法を合理的に検討することが可能になる。本研究は，表面ひび割れから内部腐食を逆推定する数値解析プログラムを逆推定するものであり，これを発展させ実構造物に適用できれば，推定した腐食状況に基づく合理的な維持管理に貢献できる。