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2018 Fiscal Year Final Research Report

Shape optimization of passive control devices for seismic retrofit considering effect on existing frame

Research Project

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Project/Area Number 16H04449
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Building structures/Materials
Research InstitutionKyoto University

Principal Investigator

Ohsaki Makoto  京都大学, 工学研究科, 教授 (40176855)

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)
Project Period (FY) 2016-04-01 – 2019-03-31
Keywords耐震補強 / 構造最適化 / ブレース / ブロック壁
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.

Free Research Field

建築構造・材料

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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Published: 2020-03-30  

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