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2016 Vol.32, Issue 11 Preview Page
Development of Seismic Fragility Curves for Slopes Using ANN-based Response Surface

인공신경망 기반의 응답면 기법을 이용한 사면의 지진에 대한 취약도 곡선 작성

Noh-Seok Park1
,
Sung-Eun Cho2*
박 노석1
,
조 성은2*
1Graduate Student, Dept. of Civil, Safety, and Environmental Engrg., Hankyong National Univ.
2Associate Prof., Dept. of Civil, Safety, and Environmental Engrg., Hankyong National Univ.
1한경대학교 토목안전환경공학과 석사과정
2한경대학교 토목안전환경공학과 부교수
*교신저자. *Corresponding Author. 
30 November 2016. pp. 31-42
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Abstract

Usually the seismic stability analysis of slope uses the pseudostatic analysis considering the inertial force by the earthquake as a static load. Geostructures such as slope include the uncertainty of soil properties. Therefore, it is necessary to consider probabilistic method for stability analysis. In this study, the probabilistic stability analysis of slope considering the uncertainty of soil properties has been performed. The fragility curve that represents the probability of exceeding limit state of slope as a function of the ground motion has been established. The Monte Carlo Simulation (MCS) has been implemented to perform the probabilistic stability analysis of slope with pseudostatic analysis. A procedure to develop the fragility curve by the pseudostatic horizontal acceleration has been presented by calculating the probability of failure based on the Artificial Neural Network (ANN) based response surface technique that reduces the required time of MCS. The results showed that the proposed method can get the fragility curve that is similar to the direct MCS-based fragility curve, and can be efficiently used to reduce the analysis time.

Keywords
Slope stability
Fragility curve
Monte Carlo Simulation
Artificial neural network

지진에 대한 사면안정 해석은 지진에 의한 관성력을 정적하중으로 고려하는 유사정적해석을 널리 사용하고 있다. 사면과 같은 지반 구조물은 지반정수의 불확실성이 포함되어 있어 확률론적 해석을 이용하여 지반정수의 불확실성을 고려해야 한다. 본 연구에서는 지반의 불확실성을 고려한 확률론적 사면안정해석을 수행하였으며, 구조물이 임의 수준의 지반 운동을 받을 때 파괴상태에 도달하는 확률을 그래프로 나타낸 취약도 곡선을 작성하였다. 유사정적해석으로 확률론적 사면안정해석을 수행하기 위해 Monte Carlo Simulation(MCS)을 시행하였다. MCS의 소요 시간을 단축하기 위하여 인공신경망 기반의 응답면 기법을 이용해 파괴확률을 산출하여 수평지진계수별 취약도 곡선을 작성하는 방법을 제시하였다. 인공신경망을 이용하여 작성한 취약도 곡선을 MCS의 결과와 비교해 본 결과 상당한 시간 절약에 비해 유사한 결과를 얻을 수 있었다.

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Information
  • Publisher :The Korean Geotechnical Society
  • Publisher(Ko) :한국지반공학회
  • Journal Title :Journal of the Korean Geotechnical Society
  • Journal Title(Ko) :한국지반공학회 논문집
  • Volume : 32
  • No :11
  • Pages :31-42
  • Received Date : 2016-08-05
  • Revised Date : 2016-09-22
  • Accepted Date : 2016-09-23
  • DOI :https://doi.org/10.7843/kgs.2016.32.11.31
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