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Development of a method for evaluating the risk of spalling of concrete cover due to rebar corrosion

Research Project

Project/Area Number 19K04554
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 22010:Civil engineering material, execution and construction management-related
Research InstitutionKagawa University

Principal Investigator

Matsushima Manabu  香川大学, 創造工学部, 特命教授 (00130302)

Co-Investigator(Kenkyū-buntansha) 車谷 麻緒  茨城大学, 理工学研究科(工学野), 准教授 (20552392)
岡崎 慎一郎  香川大学, 創造工学部, 准教授 (30510507)
Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2021: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2020: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywordsコンクリート / 鉄筋腐食 / 剥離 / 剥落 / シミュレーション / 鉄筋コンクリート / 機械学習 / 数値シミュレーション / 腐食 / ひび割れ / 破壊力学 / 電食 / 耐久性評価 / 劣化予測
Outline of Research at the Start

本研究では,塩害を受ける鉄筋コンクリート構造物を対象に,鉄筋の腐食量,かぶり厚さ,
鉄筋間隔などの条件が剥離・剥落リスクに与える影響を,特にコンクリートの内部・外部に
おけるひび割れの進展に着目して検討するものであり,大型試験体を用いた実験的検討およ
び,破壊力学に基づいた新しい腐食膨張モデルによる数値解析的検討により明らかにする.
腐食の進行モデルと,かぶりコンクリートの剥離・剥落リスクの評価については,機械学習
を用いたモデル構築を行う.

Outline of Final Research Achievements

The effects of conditions such as the amount of corrosion, cover thickness, and spacing of reinforcing bars on the risk of delamination and spalling were investigated for RC structures subjected to this salt damage. The results obtained are as follows: 1. Electrical corrosion tests were conducted on a large reinforced concrete slab specimen to identify various conditions such as cover, reinforcement conditions, and concrete performance that affect the cracking mode of reinforced concrete members; 2. The regression model for the cracking damage degree with the parameters of environment, materials used, and service life was developed with the help of machine learning model. The regression model was constructed with the aid of a machine learning model.

Academic Significance and Societal Importance of the Research Achievements

塩害を受ける鉄筋コンクリート構造物において、鉄筋腐食の程度が、かぶりコンクリートのひび割れ発生や進展性状、剥離や剥落に至るか否かを事前に判別するニーズがある。本成果により、塩害劣化したコンクリートの破壊予測モードに応じた維持管理戦略の立案に貢献することができる。

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (3 results)

All 2021 2020

All Journal Article (3 results) (of which Peer Reviewed: 3 results,  Open Access: 2 results)

  • [Journal Article] DATA DRIVEN APPROACH TO FACTOR ANALYSIS FOR SURFACE CHLORIDE CONCENTRATON OF RC STRUCTURES IN MARINE ENVIRONMENT2021

    • Author(s)
      岡崎 慎一郎、岡崎 百合子、山路 徹
    • Journal Title

      Intelligence, Informatics and Infrastructure

      Volume: 2 Issue: J2 Pages: 55-61

    • DOI

      10.11532/jsceiii.2.J2_55

    • NAID

      130008118337

    • ISSN
      2435-9262
    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Digital Image Correlation Analysis of Corrosion Crack behavior in a Reinforced Concrete Member2021

    • Author(s)
      Sho Kato, Shinichiro Okazaki, Mao Kurumatani, Manabu Matsushima
    • Journal Title

      Advances in Science and Technology

      Volume: 107 Pages: 137-143

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Predicting the Width of Corrosion-Induced Cracks in Reinforced Concrete Using a Damage Model Based on Fracture Mechanics2020

    • Author(s)
      Okazaki Shinichiro、Okuma Chisato、Kurumatani Mao、Yoshida Hidenori、Matsushima Manabu
    • Journal Title

      Applied Sciences

      Volume: 10 Issue: 15 Pages: 5272-5272

    • DOI

      10.3390/app10155272

    • Related Report
      2020 Research-status Report
    • Peer Reviewed / Open Access

URL: 

Published: 2019-04-18   Modified: 2023-01-30  

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