DATABASE IMPROVEMENT FOR MACHINE LEARNING AND APPLICATION TO STRUCTURAL CAPACITY ESTIMATION OF DETERIORATED RC MEMBERS USING OBSERVATIONAL CORROSION CRACK DISTRIBUTIONS

DOI

Bibliographic Information

Other Title
  • 機械学習用データベースの拡充および腐食ひび割れ情報を用いた劣化RC部材の耐荷力推定

Abstract

<p>Reinforced concrete (RC) structures in chloride-laden environment may have steel corrosion and corre-sponding corrosion cracks due to chloride attack. Although observed corrosion cracks provide an effective information on the status of steel corrosion inside concrete, their relationship is very complex because of many associated parameters such as structural details (e.g. cover and rebar arrangement). In this study, steel corrosion distributions in longitudinal and transverse directions have been obtained through corrosion ex-periments of RC members with different structural details. Parameters to represent the 2D-stochastic field associated with the steel corrosion distribution were identified. With the aid of 3D-finite element analysis, a database consisting of the relationship between steel corrosion and corrosion cracks for machine learning (pix2pix) was developed numerically. Finally, given corrosion crack distributions observed in the deterio-rated RC members and structural details, the structural capacity can be estimated. </p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390294113692207232
  • DOI
    10.11532/jsceiii.3.j2_117
  • ISSN
    24359262
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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