Journal of the Korean Geotechnical Society (한국지반공학회논문집)

Korean Geotechnical Society (한국지반공학회)
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Prediction of Slope Failure Arc Using Multilayer Perceptron

다층 퍼셉트론 신경망을 이용한 사면원호 파괴 예측

  • Ma, Jeehoon (Dept. of Civil and Environmental Eng., Yonsei Univ.) ;
  • Yun, Tae Sup (Dept. of Civil and Environmental Eng., Yonsei Univ.)
  • 마지훈 (연세대학교 건설환경공학과) ;
  • 윤태섭 (연세대학교 건설환경공학과)
  • Received : 2022.06.20
  • Accepted : 2022.08.12
  • Published : 2022.08.31
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Abstract

Multilayer perceptron neural network was trained to determine the factor of safety and slip surface of the slope. Slope geometry is a simple slope based on Korean design standards, and the case of dry and existing groundwater levels are both considered, and the properties of the soil composing the slope are considered to be sandy soil including fine particles. When curating the data required for model training, slope stability analysis was performed in 42,000 cases using the limit equilibrium method. Steady-state seepage analysis of groundwater was also performed, and the results generated were applied to slope stability analysis. Results show that the multilayer perceptron model can predict the factor of safety and failure arc with high performance when the slope's physical properties data are input. A method for quantitative validation of the model performance is presented.

사면의 안전율과 임계활동면을 다층 퍼셉트론 신경망(multi-layer perceptron, MLP)을 이용하여 구할 수 있도록 훈련하였다. 사면의 형상은 한국의 설계기준을 참고한 단순 사면으로, 건조한 경우와 지하수위가 존재하는 경우를 모두 고려하였으며 사면을 구성하는 토질의 물성은 세립분을 포함한 사질토로 고려하였다. 훈련에 필요한 데이터를 만들 때 한계평형해석법을 이용하여 42,000가지 경우의 사면안정해석을 수행하였고, 지하수위가 고려된 도메인의 해석에서 불포화토의 모관흡수력으로 인한 유효응력 증가를 고려하였다. 지하수와 유효응력의 분포를 사면안정해석에 적용할 수 있도록 정상상태 침투 해석을 수행하였다. 사면을 표현하는 물성을 입력하면 안전율과 원호 파괴면을 예측할 수 있는 MLP 모델과 모델의 성능을 정량적으로 평가할 수 있는 방법을 제시하였다.

Keywords

Acknowledgement

본 연구는 한국연구재단(Nos. 2020R1A2C1014815, NRF-2021R1A5A1032433)과 한국토지주택공사 토지주택연구원의 지원으로 연구비 지원을 받아 수행된 것으로 해당 부처들에 깊은 감사를 드립니다.

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