한국지반신소재학회논문집 (Journal of the Korean Geosynthetics Society)

  • 제21권2호
  • /
  • Pages.21-30
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  • 2022
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  • 2508-2876(pISSN)
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  • 2287-9528(eISSN)
한국지반신소재학회 (Korean Geosynthetics Society)
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심층인공신경망을 이용한 암반사면의 전단강도 산정

Calculation of Shear Strength of Rock Slope Using Deep Neural Network

  • Lee, Ja-Kyung (Dept. of Civil Engineering, Korea Maritime and Ocean Univ.) ;
  • Choi, Ju-Sung (Dept. of Civil Engineering, Korea Maritime and Ocean Univ.) ;
  • Kim, Tae-Hyung (Dept. of Civil Engineering, Korea Maritime and Ocean Univ.) ;
  • Geem, Zong Woo (Dept. of Smart City & Energy, Gachon Univ.)
  • 투고 : 2022.05.02
  • 심사 : 2022.06.16
  • 발행 : 2022.06.30
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초록

전단강도는 암반 비탈면 안정성 평가에서 가장 중요한 지표이다. 일반적으로 기존 문헌자료, 역해석, 실험 등의 결과를 비교하여 산정한다. 암반 비탈면에서의 전단강도는 불연속면의 상태와 관련된 변수를 추가로 고려해야 한다. 이 변수들은 시추조사를 통해 여부를 파악하는 것이 어려울뿐더러 전단강도와의 정확한 관계를 찾아내기도 어렵다. 본 연구에서는 역해석을 통해 산정된 데이터를 이용했다. 기존 고려되었던 변수들의 관계를 딥러닝에 접목시켜 전단강도 산정에 적합한지 그 가능성을 모색하였다. 비교를 위해 기존에 사용되는 간단한 선형회귀(Linear Regression) 모델과 딥러닝 알고리즘인 심층인공신경망(DNN) 모델을 사용하였다. 각 분석 모델은 비슷한 예측결과를 도출해내었지만 미세한 차이로 DNN의 설명력이 개선된 결과를 나타내었다.

Shear strength is the most important indicator in the evaluation of rock slope stability. It is generally estimated by comparing the results of existing literature data, back analysis, experiments and etc. There are additional variables related to the state of discontinuity to consider in the shear strength of the rock slope. It is difficult to determine whether these variables exist through drilling, and it is also difficult to find an exact relationship with shear strength. In this study, the data calculated through back analysis were used. The relationship between previously considered variables was applied to deep learning and the possibility for estimating shear strength of rock slope was explored. For comparison, an existing simple linear regression model and a deep learning algorithm, a deep neural network(DNN) model, were used. Although each analysis model derived similar prediction results, the explanatory power of DNN was improved with a small differences.

키워드

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