Shape optimization of passive control devices for seismic retrofit considering effect on existing frame
| Project/Area Number |
16H04449
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Building structures/Materials
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| Research Institution | Kyoto University |
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Principal Investigator |
Ohsaki Makoto 京都大学, 工学研究科, 教授 (40176855)
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| Co-Investigator(Kenkyū-buntansha) |
田川 浩 広島大学, 工学研究科, 教授 (70283629)
高木 次郎 首都大学東京, 都市環境科学研究科, 准教授 (90512880)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥15,340,000 (Direct Cost: ¥11,800,000、Indirect Cost: ¥3,540,000)
Fiscal Year 2018: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
Fiscal Year 2017: ¥5,590,000 (Direct Cost: ¥4,300,000、Indirect Cost: ¥1,290,000)
Fiscal Year 2016: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
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| Keywords | 耐震補強 / 構造最適化 / ブレース / ブロック壁 / 建築構造・材料 / 耐震設計 / 補強ブロック / 形状最適化 |
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| Outline of Final Research Achievements |
A shape optimization method has been presented for latticed blocks for seismic retrofit. The blocks can easily be installed in the existing building, because seismic shear force is mainly supported with compressive forces in the block and contact to the existing beams and columns. The performance of the optimized blocks has been confirmed through experiment of a 3D-printed small-scale model. Furthermore, new types of braces such as compression brace with double steel tubes and flexural yielding brace with H-section have been proposed, and their performances have been confirmed through loading tests. Furthermore, a method has been proposed to evaluate structural performances of decent solutions for optimal brace placement problem and classify them using heuristic approach and machine learning.
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| Academic Significance and Societal Importance of the Research Achievements |
既存の建築建物の耐震性能を向上させるため，主に圧縮力と既存骨組への接触力で層せん断力に抵抗するブレースの新しい形式を提案し，数値解析によって，その性能を最適化するとともに実験で検証した。本研究の成果により，建物の使用を継続しながら，火器の使用や騒音をともなわずにブレースを簡便に設置でき，耐震性能を向上させることができる。また，ブレースの最適な配置を，設計者の勘と経験に頼らず，最適化や機械学習に基づく数理的な手法で求めることが可能となった。
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Report
(4 results)
Research Products
(25 results)
