Journal of the Earthquake Engineering Society of Korea (한국지진공학회논문집)

Earthquake Engineering Society of Korea (한국지진공학회)
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Predictive Models of Deep Shear Wave Velocity Profiles at Excavated Rock Sites in Korea

국내 굴착 암반 부지에 대한 심부 전단파속도 주상도 예측 모델 개발

  • Kim, Jieun ( Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Kim, Byungmin ( Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Cho, Youngkyu ( Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology)
  • 김지은 (울산과학기술원 지구환경도시건설공학과) ;
  • 김병민 (울산과학기술원 지구환경도시건설공학과) ;
  • 조영규 (울산과학기술원 지구환경도시건설공학과)
  • Received : 2024.11.16
  • Accepted : 2024.12.09
  • Published : 2025.01.01
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Abstract

IIn the context of site response analysis, the use of shear wave velocity (VS) profiles that consider the seismological rock (VS ≥ 3,000 m/s) depth is recommended. This study proposes regression analysis and machine learning-based models to predict deep VS profiles for a specialized excavated rock site in South Korea. The regression model was developed by modifying mathematical expressions from a previous study and analyzing the correlation between VS50 and model variables to predict deep VS beyond 50 m. The machine learning models, designed using tree-based algorithms and a fully connected hierarchical structure, were developed to predict VS from 51 m to 300 m at 1 m intervals. These models were validated by comparing them with measured deep VS profiles and accurately estimating the trend of deep VS variations. The proposed prediction models are expected to improve the accuracy of ground motion predictions for a specialized excavated rock site in Korea.

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Acknowledgement

본 논문은 한국수력원자력(주)에서 재원을 부담하여 "제 2022-기술-03호"에서 수행한 연구입니다. 머신러닝 기반의 예측 모델 개발과 관련하여 도움을 주신 교토대학교 김지송 박사님께 감사를 표합니다.