[HTML][HTML] Feedback on a shared big dataset for intelligent TBM Part II: Application and forward look

JB Li, ZY Chen, X Li, LJ Jing, YP Zhang, HH Xiao… - Underground …, 2023 - Elsevier
This review discusses the application scenarios of the machine learning-supported
performance prediction and the optimization efficiency of tunnel boring machines (TBMs) …

[HTML][HTML] Real-time rock mass condition prediction with TBM tunneling big data using a novel rock–machine mutual feedback perception method

Z Wu, R Wei, Z Chu, Q Liu - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
Real-time perception of rock mass information is of great importance to efficient tunneling
and hazard prevention in tunnel boring machines (TBMs). In this study, a TBM–rock mutual …

Examining feasibility of developing a rock mass classification for hard rock TBM application using non-linear regression, regression tree and generic programming

A Salimi, J Rostami, C Moormann… - Geotechnical and …, 2018 - Springer
Geotechnical and geological parameters have the greatest impact on the performance of
hard rock tunnel boring machines (TBMs). This includes the rock and rock mass properties …

Development of a rock mass characteristics model for TBM penetration rate prediction

Q Gong, J Zhao - International journal of Rock mechanics and mining …, 2009 - Elsevier
The TBM tunneling process in hard rock is actually a rock or rock mass breakage process,
which determines the efficiency of tunnel boring machine (TBM). On the basis of the rock …

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 …

Prediction of hard rock TBM penetration rate using particle swarm optimization

S Yagiz, H Karahan - International Journal of Rock Mechanics and Mining …, 2011 - Elsevier
The aim of this study is to predict the performance of tunnel boring machines (TBMS) using
particle swarm optimization technique (PSO). With this aim, a database including intact rock …

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 …

Application of rock mass classification systems for performance estimation of rock TBMs using regression tree and artificial intelligence algorithms

A Salimi, J Rostami, C Moormann - Tunnelling and Underground Space …, 2019 - Elsevier
Existing rock mass classification systems, such as Rock Quality Index “Q”, Geological
Strength Index (GSI), and Rock Mass Rating (RMR) are often used in many empirical design …

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 …

Investigations into the cutting characteristics of CCS type disc cutters and the comparison between experimental, theoretical and empirical force estimations

D Tumac, C Balci - Tunnelling and Underground Space Technology, 2015 - Elsevier
A new model is suggested in this study to predict normal and rolling forces acting on CCS
type disc cutters by modifying an empirical model developed by Bilgin (1977) for V type disc …