Data-Driven Prediction of Stability of Rock Tunnel Heading: An Application of Machine Learning Models

Data-Driven Prediction of Stability of Rock Tunnel Heading: An Application of Machine Learning Models

In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield criterion. The HB model was developed to capture the failure criterion of rock masses. To provide the datasets for an AN...

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Bibliographic Details
Main Authors: Chayut Ngamkhanong, Suraparb Keawsawasvong, Thira Jearsiripongkul, Lowell Tan Cabangon, Meghdad Payan, Kongtawan Sangjinda, Rungkhun Banyong, Chanachai Thongchom
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Infrastructures
Subjects:
tunnel heading
rock mass
Hoek-Brown
underground opening
limit analysis
artificial neural network
Online Access:https://www.mdpi.com/2412-3811/7/11/148

Internet

https://www.mdpi.com/2412-3811/7/11/148

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