Predicting Roadway Surrounding Rock Deformation and Plastic Zone Depth Using BP Neural Network

DOI

10.2991/iccet-15.2015.305How to use a DOI?

Keywords

roadway surrounding rock deformation; depth of plastic zone; BP neural network; prediction

Abstract

It is a complex nonlinear problem to analyze the interaction between bind and the deformation of surrounding rocks and the depth of plastic zones as well as the deformation caused by destruction. This study tackles this problem by taking into account the size of roadway section, burial depth, rock parameters and the in homogeneity of surrounding rock. The software, namely--FLAC3D has been used perform the numerical analysis. The sample data that affect the deformation and plastic zone size of the surrounding rock have been investigated. The BP Neural Network Predictive Model has been developed to solve the nonlinear mapping issue. With the strength of the artificial neural network, the prime deformation and the plastic zone range of the surrounding rocks caused by the roadway excavation were obtained. The developed predictive model has further been tested with a case study on the roadway with the Jalainur northern iron ore. The predictions of the ore’s deformation and plastic zone range of surrounding rock are found to be consistent with the field observations.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Jianying Zhang
AU  - Yucheng Zhao
AU  - Mingyuan Liu
PY  - 2015/11
DA  - 2015/11
TI  - Predicting Roadway Surrounding Rock Deformation and Plastic Zone Depth Using BP Neural Network
BT  - Proceedings of the 5th International Conference on Civil Engineering and Transportation 2015
PB  - Atlantis Press
SP  - 1636
EP  - 1642
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccet-15.2015.305
DO  - 10.2991/iccet-15.2015.305
ID  - Zhang2015/11
ER  -