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Machine Learning based Seismic Response Prediction Methods for Steel Frame Structures

기계학습 기반 강 구조물 지진응답 예측기법

  • Lee, Seunghye (Deep Learning Architecture Research Center, Dept. of Architectural Engineering, Sejong University) ;
  • Lee, Jaehong (Deep Learning Architecture Research Center, Dept. of Architectural Engineering, Sejong University)
  • 이승혜 (딥러닝 건축연구소, 세종대학교 건축공학과) ;
  • 이재홍 (딥러닝 건축연구소, 세종대학교 건축공학과)
  • Received : 2024.05.28
  • Accepted : 2024.06.04
  • Published : 2024.06.15

Abstract

In this paper, machine learning models were applied to predict the seismic response of steel frame structures. Both geometric and material nonlinearities were considered in the structural analysis, and nonlinear inelastic dynamic analysis was performed. The ground acceleration response of the El Centro earthquake was applied to obtain the displacement of the top floor, which was used as the dataset for the machine learning methods. Learning was performed using two methods: Decision Tree and Random Forest, and their efficiency was demonstrated through application to 2-story and 6-story 3-D steel frame structure examples.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2023R1A2C2003310).

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