Multi-step Inverse Analysis for Rebar Corrosion using Genetic Algorithm and Boundary Element Method

• Minagawa Koichi

  Intelligent Material and Mechanics System, Toyo University

• Hayabusa Keisuke

  Ebara Research. Co., LTD.

• Suga Kazuhiro

  CCMR, Toyo University

• Ridha M.

  CCMR, Toyo University

• Amaya Kenji

  Department of Mechanical and Environmental Informatics, Tokyo Institute of Technology

• Aoki Shigeru

  Department of Computational Engineering and Science, Toyo University

Bibliographic Information

Other Title

• 遺伝的アルゴリズムと境界要素法を用いた多段階鉄筋腐食逆解析
• イデンテキ アルゴリズム ト キョウカイ ヨウソホウ オ モチイタ タダンカイ テッキン フショク ギャクカイセキ

Abstract

This research proposes an effective inverse analysis technique for solving an inverse problem to detect corrosion in reinforced concrete non-destructively from potentials on a concrete surface. The technique can detect the number, the shape and the location of corrosion without particular assumption with GA (genetic algorithm), and increases accuracy of solution gradually if necessary. The following three strategies achieve the proposed technique: (1) Control of analysis precision, i.e. coarseness of BEM (boundary element method) meshes, depending on required precision of solution. (2) Use of the net elements for BEM for decreasing the number of elements for steels. (3) Analysis with higher precision only within detected corrosion area on lower precise analysis. We performed a numerical simulation to solve an inverse problem for detecting steel corrosion in concrete with the proposed technique. The result showed that the proposed method could detect corrosion with high accuracy. The calculation time of the proposed method was about 1/100 in comparison with that of the previously proposed method.

Journal

• Zairyo-to-Kankyo

  Zairyo-to-Kankyo 57 (6), 282-287, 2008

  Japan Society of Corrosion Engineering

Keywords

• corrosion
• non-destructive inspection
• inverse analysis
• boundary element method
• genetic algorithm
• net element

Details

• CRID: 1390282681236934144
• NII Article ID: 10021170911
• NII Book ID: AN10235427
• DOI: 10.3323/jcorr.57.282
• ISSN: 18819664
• ISSN: 09170480
• NDL BIB ID: 9547398
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I9547398
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed