Development of a Network Expert System for Safety Analysis of Structures Adjacent to Tunnel Excavation Sites

터널굴착 현장에 인접한 지상구조물의 안전성 평가용 전문가 시스템의 개발

  • 배규진 (한국건설기술연구원 지반연구실) ;
  • 김창용 (한국건설기술연구원 지반연구실) ;
  • 신휴성 (한국건설기술연구원) ;
  • 홍성환 (한국건설기술연구원)
  • Published : 1999.12.01


Ground settlements induced by tunnel excavation cause the foundations of the neighboring superstructures to deform. An expert system called NESASS was developed to analyze the structural safety of such superstructures. NESASS predicts the trend of ground settlements to be resulted from tunnel excavation and carries out a safety analysis for superstructures on the basis of the predicted ground settlements. Using neural network techniques, NESASS learns a data base consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure and, in turn, determines the safety of the structure. In addition, NESASS predicts the patterns of cracks to be formed on the structure using Dulacskas model for crack evaluation. In this study, the ground settlements measured from the Seoul subway construction sites were collected and sorted with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to verify the reliability of the proposed neural network structure. A comparison of the ground settlement trends predicted by NESASS with the measured ones indicates that NESASS leads to reasonable predictions. An examples is presented in this paper where NESASS is used to evaluate the safety of a structure subject to deformation due to tunnel excavation near to the structure.