E-Defense Shake-table Test of a Building Designed for Post-disaster Functionality-Reference-Cited by-同舟云学术

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E-Defense Shake-table Test of a Building Designed for Post-disaster Functionality

Published:2021-02-03 Issue: Volume: Page:1-22
ISSN:1363-2469
Container-title:Journal of Earthquake Engineering
language:en
Short-container-title:Journal of Earthquake Engineering

Author:

Yeow Trevor Zhiqing¹^ORCID,Kusunoki Koichi¹^ORCID,Nakamura Izumi²,Hibino Yo³^ORCID,Fukai Satoru⁴,Safi Walid Ahmad⁵

Affiliation:

1. Earthquake Research Institute, The University of Tokyo, Tokyo, Japan

2. Earthquake Disaster Mitigation Research Division, National Research Institute for Earth Science and Disaster Resilience, Tsukuba, Japan

3. Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan

4. Structural Engineering Division, Nikken Sekkei Ltd, Tokyo, Japan

5. Graduate School of Engineering, Hiroshima University, Hiroshima, Japan

Funder

National Research Institute for Earth Science and Disaster Resilience

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/13632469.2020.1865219

Reference18 articles.

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Numerical simulation of the 2010 4-story reinforced concrete structure tested on the E-defense shake table;Engineering Structures;2024-05

2. Investigations for understanding the failure mechanism associated with vibration effects on open-pit slopes constituting of sand and gravel mixtures;Bulletin of Engineering Geology and the Environment;2024-03-11

3. Data Collection Using Terrestrial Laser Scanners from the Shake-Table Test of a Full-Scale Reinforced Concrete Building;Journal of Structural Engineering;2024-02

4. Experiment Research on Complex Optimization Algorithm-Based Adaptive Iterative Learning Control for Electro-Hydraulic Shaking Tables;Electronics;2023-04-10

5. Development of a Deep Learning-Based Anomaly Detection System for Structures;Lecture Notes in Civil Engineering;2023

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