| Project/Area Number |
18K14504
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 40020:Wood science-related
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| Research Institution | Shizuoka University (2019-2021)
Forest Research and Management Organization (2018) |
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Principal Investigator |
Ogawa Keita 静岡大学, 農学部, 助教 (10805021)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 木質構造 / 木材 / 合板 / 釘接合 / せん断 / 木質接合部 / 釘 / 性能評価 / 釘接合部 / せん断性能 / 試験方法 |
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| Outline of Final Research Achievements |
In this study, reserch plans that removed the influence of the physical properties of the specimens as much as possible was designed, in order to collect the data that allowed discussion of the influence of the test method on the evaluation results lateral properties of nailed joints between wood and plywood. For example, it was quantitatively shown that the ASTM method showed more variation in the initial loading range than the JAS method, and that the panel type specimen reached failure with relatively smaller displacements than the others.
In addition, the reason for occuring the variation between the methods of ASTM and JAS were clarified using simulations. By constructing a program using random numbers, it was shown that the variation can be explained as a counterbalancing effect of the use of multiple nails in the same specimen.
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| Academic Significance and Societal Importance of the Research Achievements |
木材と合板との釘接合は，木質構造における重要な接合部であり，そのせん断性能の把握は大きな関心事である。様々な利点を背景に，現在では多くのせん断試験の評価試験方法が存在しているが，試験方法の違いが評価結果に及ぼす影響を明らかにすることが重要である。これまでの長年の木質構造の研究の中で，釘接合部のせん断性能について多くのデータが蓄積されているが，今後はこれらのデータの活用にさらなる関心が集まることが予想される。本研究で得られた知見は，これら既存のデータの有効活用に資することが期待できる。
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