Prediction of TBM tunnel segment lining forces using ANN technique

This paper presents development of artificial neural network(ANN) based prediction method for section forces of TBM tunnel segment lining in an effort to develop an automatized design technique. A series of design cases were first developed and subsequently analyzed using the two-ring beam finite element model. The results were then used to form a database for use as training and validation data sets for ANN development. Using the database, optimized ANNs were developed that can readily be used to predict maximum sectional forces and their distributions. It is shown that the compute maximum section forces and their distributions by the developed ANNs are almost identical to the computed by the two-ring beam finite element model, implying that the developed ANNs can be used as design tools which expedite routine design calculation process. The results of this study indicate that the neural network model can be effectively used as a reliable and simple predictive tool for the prediction of segment sectional forces for design.

keywords: TBM Tunnel, Segment lining, Finite element analysis, 2-Ring Beam-Spring Model, Artificial neural network, TBM 세그먼트라이닝, 유한요소해석, 2-Ring Beam 모델, 인공신경망

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Article Contents

Vol.16 No.1

Prediction of TBM tunnel segment lining forces using ANN technique

Abstract

Reference

(사)한국터널지하공간학회