Wind and Structures

  • 제36권6호
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  • Pages.379-392
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  • 2023
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Predicting the lateral displacement of tall buildings using an LSTM-based deep learning approach

  • Bubryur Kim (Department of Robot and Smart System Engineering, Kyungpook National University) ;
  • K.R. Sri Preethaa (Department of Computer Science and Engineering, KPR Institute of Engineering and Technology) ;
  • Zengshun Chen (School of Civil Engineering, Chongqing University) ;
  • Yuvaraj Natarajan (Department of Robot and Smart System Engineering, Kyungpook National University) ;
  • Gitanjali Wadhwa (Department of Computer Science and Engineering, KPR Institute of Engineering and Technology) ;
  • Hong Min Lee (Engineering Co., Ltd.)
  • 투고 : 2022.08.08
  • 심사 : 2023.01.12
  • 발행 : 2023.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

Structural health monitoring is used to ensure the well-being of civil structures by detecting damage and estimating deterioration. Wind flow applies external loads to high-rise buildings, with the horizontal force component of the wind causing structural displacements in high-rise buildings. This study proposes a deep learning-based predictive model for measuring lateral displacement response in high-rise buildings. The proposed long short-term memory model functions as a sequence generator to generate displacements on building floors depending on the displacement statistics collected on the top floor. The model was trained with wind-induced displacement data for the top floor of a high-rise building as input. The outcomes demonstrate that the model can forecast wind-induced displacement on the remaining floors of a building. Further, displacement was predicted for each floor of the high-rise buildings at wind flow angles of 0° and 45°. The proposed model accurately predicted a high-rise building model's story drift and lateral displacement. The outcomes of this proposed work are anticipated to serve as a guide for assessing the overall lateral displacement of high-rise buildings.

키워드

과제정보

This research was supported by Kyungpook National University Research Fund, 2021.

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