| Project/Area Number |
18K04422
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 23010:Building structures and materials-related
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| Research Institution | Tohoku University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
梶原 浩一 国立研究開発法人防災科学技術研究所, 地震減災実験研究部門, 総括主任研究員 (10450256)
長江 拓也 名古屋大学, 減災連携研究センター, 准教授 (90402932)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2019: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 鉄筋コンクリート / ひび割れ / 損傷量 / 深層学習 / ひび割れ進展 / 幾何学的部材変形 / ひび割れ間隔 / ひび割れ定常状態 / ひび割れ幅分布 / 外力作用条件 |
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| Outline of Final Research Achievements |
The development of a damage measurement system to be applied to loading tests was carried out. As a preliminary study, full-scale dynamic loading tests of an Steel structure sub-assemblies with RC slab and static loading tests of RC walls were conducted. A measurement device using a not-expensive action cam was developed to measure how the amount of damage, that is the combination of crack width and crack length named as "crack width distribution model", changes as the member drift-ratio increases. In this research, the characteristics of crack detection techniques using A.I. as well as general image processing were verified. A simple damage evaluation method was developed for wall members as well as for column and beam members, for which the evaluation of damage propagation by a simplified method has been studied in the past, and the accuracy of the method was verified.
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| Academic Significance and Societal Importance of the Research Achievements |
RC部材の地震損傷を簡易なモデルで推定する手法を提案し，「ひび割れ幅－ひび割れ長さ」関係を「ひび割れ幅分布関数」として対数正規分布でモデル化し，計算負荷の小さい方法で部材損傷量（ひび割れ幅，ひび割れ長さ）を推定する方法を確立した。また，推定手法の精度検証にあたって，A.I.を用いた画像処理技術に基づく損傷量計測・評価技術に関する近年の研究動向を踏まえ，A.I.を用いた損傷量評価における撮影環境条件および解析フローを提案し，経年劣化損傷と地震損傷を区別して評価する技術を開発した。これらの技術は，ユーザー指向型の性能評価型設計，特に修復性能評価の普及・促進に資する基盤技術となり得るものである。
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