Rectangular tunnel heading stability in three dimensions and its predictive machine learning models  

作　　者：Jim Shiau Suraparb Keawsawasvong Van Qui Lai Thanachon Promwichai Viroon Kamchoom Rungkhun Banyong 

机构地区：[1]School of Engineering,University of Southern Queensland,QLD,Toowoomba,4350,Australia [2]Department of Civil Engineering,Thammasat School of Engineering,Thammasat University,Klong Luang,Pathumthani,12120,Thailand [3]Faculty of Civil Engineering,Ho Chi Minh City University of Technology(HCMUT),Ho Chi Minh City,Viet Nam [4]Vietnam National University Ho Chi Minh City(VNU-HCM),Ho Chi Minh City,Viet Nam [5]Excellent Centre for Green and Sustainable Infrastructure,Department of Civil Engineering,School of Engineering,King Mongkut's Institute of Technology Ladkrabang(KMITL),Bangkok,Thailand

出　　处：《Journal of Rock Mechanics and Geotechnical Engineering》2024年第11期4683-4696,共14页岩石力学与岩土工程学报（英文）

基　　金：supported by the Thailand Science Research and Innovation Fundamental Fund fiscal year 2023;The fifth author (V.Kamchoom)acknowledges the financial support from the National Science,Research and Innovation Fund (NSRF)at King Mongkut's Institute of Technology Ladkrabang (KMITL),Thailand (Grant No.FRB66065/0258-RE-KRIS/FF66/53);the Climate Change and Climate Variability Research in Monsoon Asia (CMON3)from the National Research Council of Thailand (NRCT) (Grant No.N10A650844);the National Natural Science Foundation of China (NSFC).

摘　　要：Tunnel heading stability in two dimensions(2D)has been extensively investigated by numerous scholars in the past decade.One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization.Nevertheless,it is possible to study the stability of tunnels in three dimensions(3D)with a rectangular shape using finite element limit analysis(FELA)and a nonlinear programming technique.This paper employs 3D FELA to generate rigorous solutions for stability numbers,failure mechanisms,and safety factors for rectangular-shaped tunnels.To further explore the usefulness of the produced results,multivariate adaptive regression spline(MARS)is used for machine learning of big dataset and development of design equations for practical design applications.The study should be of great benefit to tunnel design practices using the developed equations provided in the paper.

关 键 词：Wide rectangular tunnel Finite element limit analysis(FELA) Multivariate adaptive regression spline(MARS) Three dimensions(3D) Stability analysis 

分 类 号：U456[建筑科学—桥梁与隧道工程]