Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

[HTML][HTML] Rock brittleness indices and their applications to different fields of rock engineering: A review

F Meng, LNY Wong, H Zhou - Journal of Rock Mechanics and …, 2021 - Elsevier
Brittleness is an important parameter controlling the mechanical behavior and failure
characteristics of rocks under loading and unloading conditions, such as fracability …

[HTML][HTML] Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization

J Zhou, Y Qiu, S Zhu, DJ Armaghani, M Khandelwal… - Underground …, 2021 - Elsevier
The advance rate (AR) of a tunnel boring machine (TBM) under hard rock conditions is a key
parameter in the successful implementation of tunneling engineering. In this study, we …

Prediction of rock mass parameters in the TBM tunnel based on BP neural network integrated simulated annealing algorithm

B Liu, R Wang, G Zhao, X Guo, Y Wang, J Li… - … and Underground Space …, 2020 - Elsevier
The prediction of rock mass parameters is of great significance in ensuring the safety and
efficiency of tunnel boring machine (TBM) tunnel construction. Previous studies have …

Performance prediction of hard rock TBM using Rock Mass Rating (RMR) system

JK Hamidi, K Shahriar, B Rezai, J Rostami - Tunnelling and Underground …, 2010 - Elsevier
RMR is a simple rock mass classification system and is often used for characterization and
design purposes in preliminary stages of mining and civil engineering practices. However …

Machine learning to inform tunnelling operations: Recent advances and future trends

BB Sheil, SK Suryasentana… - Proceedings of the …, 2020 - icevirtuallibrary.com
The proliferation of data collected by modern tunnel-boring machines (TBMs) presents a
substantial opportunity for the application of machine learning (ML) to support the decision …

Investigation into the effects of different rocks on rock cuttability by a V-type disc cutter

C Balci, D Tumaç - Tunnelling and underground space technology, 2012 - Elsevier
This paper is about to investigate the effects of different rock structural properties and a V-
type disc cutter on rock cuttability. The cutter having 381mm in diameter, 90° edge angle and …

Improved support vector regression models for predicting rock mass parameters using tunnel boring machine driving data

B Liu, R Wang, Z Guan, J Li, Z Xu, X Guo… - … and Underground Space …, 2019 - Elsevier
The sensitivity of tunnel boring machines (TBMs) to complex rock mass parameters makes
the accurate and reliable prediction of these parameters crucial for the selection of …

Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic

E Ghasemi, S Yagiz, M Ataei - Bulletin of Engineering Geology and the …, 2014 - Springer
Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in
the economic and time planning of tunneling projects. In the past years, various empirical …

Correlation of rock cutting tests with field performance of a TBM in a highly fractured rock formation: a case study in Kozyatagi-Kadikoy metro tunnel, Turkey

C Balci - Tunnelling and Underground Space Technology, 2009 - Elsevier
This paper presents and discusses detailed field and laboratory studies concerning
boreability prediction of tunnel boring machines (TBMs) used in Kozyatagi-Kadikoy metro …