2023 Fiscal Year Final Research Report
Structural performance evaluation of real civil infrastructure by merging dense point cloud data into FE analysis
| Project/Area Number |
21K04230
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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 22020:Structure engineering and earthquake engineering-related
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| Research Institution | Hokkaido University (2022-2023)
Kitami Institute of Technology (2021) |
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Principal Investigator |
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | 点群データ / SfM / 構造解析 / FEM |
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| Outline of Final Research Achievements |
We developed a method to construct a finite element model that can calculate the displacement and stress distribution of a structural member from point cloud data acquired by SfM (Structure from Motion), which is 3D data that can be used to manage civil infrastructures. The coordinate data of the point cloud model is used as nodal points in units of a voxel. The point cloud data was converted into 2D cross sections at regular intervals in the axial direction of the member, each section was divided into 2D Delaunay sections, and solid elements were created by connecting adjacent sections and nearest neighbor points. The point cloud FE model constructed with this method enables linear static analysis of structures with locally reduced thickness and shows the possibility of quantitatively understanding the stress state of existing structures.
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| Free Research Field |
土木工学，構造工学
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| Academic Significance and Societal Importance of the Research Achievements |
近年，構造物の維持管理に3次元データが活用されている．SfM(Structure from Motion)は通常のデジタルカメラで撮影した静止画や動画から3次元点群データを構築することができて，経済性や汎用性に優れている．一方，現状では点群データは構造物の外面の変状を確認し，健全性を定性的に評価することが主な用途である．本研究は，構造物の維持管理をさらに効率化するため，点群データから構造解析可能な数値モデルを作成して，健全性を定量的に把握する方法であり，表面的には劣化が進行していても，実際の保有耐力を適切に評価し，構造物の長寿命化につながる技術で，有用性があり社会的意義を有する．
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