Journal of the Korean Geotechnical Society (한국지반공학회논문집)

Korean Geotechnical Society (한국지반공학회)
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Prediction of Major Parameters of Surface Settlements Due to Tunnelling

터널굴착으로 인한 지반침하의 주요 영향 인자 예측

  • Kim, Chang-Yong (Member, Senior Researcher, Civil Engrg., Division, Korea Institute of Construction Technology) ;
  • Park, Chi-Hyun (Member, Researcher, Civil Engrg., Division, Korea Institute of Construction Technology)
  • Published : 2002.06.01
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Abstract

Although there are several empirical and semi-empirical formulae available for predicting ground surface settlement, most of them do not simultaneously take into consideration all the relevant factors, resulting in inaccurate predictions. In this study, an artificial neural network (ANN) is incorporated with 113 of monitored field results to predict surface settlement for a tunnel site with prescribed conditions. To achieve this, a format for a database of monitored field data is first proposed and then used for sorting out a variety of monitored data sets available in Korea Institute of Construction Technology. An optimal neural network model is suggested through preliminary parametric studies and introduces a concept of RSE (Yang and Zhang, 1997) in sensitivity analysis for various major factors affecting the surface settlement in tunnelling. It is seen in some examples that the RSE rationally enables to recognize the most significant factors of all the contributing factors. Two verification examples are undertaken with the trained ANN using the database created in this study. It is shown from the examples that the ANN has adequately recognized the characteristics of the monitored data sets retaining a generality fur further prediction.

지반의 지표침하를 예측하는 여러가지 경험식들이 있지만, 관련인자들을 동시에 고려하지 못함으로 인하여 불확실한 예측결과를 가져온다. 본 연구에서는 113개의 현장계측자료를 이용한 인공신경 망으로 조건에 따른 터널현장의 지표침하를 예측하였다. 지표침하 예측을 위한 현장자료의 입력양식을 제안하였으며, 인자학습을 통해 최적의 인공신경 망 모델을 구성하고 RSE의 개념을 통해 터널굴착으로 인한 지표침하에 영향을 미치는 주요인자들을 분석하였다. 본 연구에서 구성한 데이터베이스를 이용하여 인공신경 망 엔진을 학습하고 두 가지 현장자료를 통해 검증한 결과, 계측자료의 특성을 효과적으로 반영하는 것을 확인하였다.

Keywords

References

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