Use of Rock Mass Fabric Index in Fuzzy Environment for TBM Performance Prediction

2014 ◽  
pp. 1019-1022
Author(s):  
Mansour Hedayatzadeh ◽  
Jafar Khademi Hamidi
Keyword(s):  
Rock Mass ◽  
Performance Prediction ◽  
Tbm Performance ◽  
Fuzzy Environment

Geological and mechanical rock mass conditions for TBM performance prediction. The case of “La Maddalena” exploratory tunnel, Chiomonte (Italy)

2018 ◽  
Vol 77 ◽  
pp. 115-126 ◽  
Author(s):  
Giacomo Armetti ◽  
Maria Rita Migliazza ◽  
Federica Ferrari ◽  
Andrea Berti ◽  
Paolo Padovese
Keyword(s):  
Rock Mass ◽  
Performance Prediction ◽  
Tbm Performance

scholarly journals From Exploratory Tunnel to Base Tunnel: Hard Rock TBM Performance Prediction by Means of a Stochastic Approach

2020 ◽  
Vol 53 (12) ◽  
pp. 5473-5487 ◽  
Author(s):  
Andrea Rispoli ◽  
Anna Maria Ferrero ◽  
Marilena Cardu
Keyword(s):  
Performance Prediction ◽  
Early Stage ◽  
Tunnel Boring Machine ◽  
Stochastic Approach ◽  
Critical Issue ◽  
Utilization Factor ◽  
Tbm Performance ◽  
Factors Affecting ◽  
Tunnel Section ◽  
Input Variables

AbstractTunnel boring machine (TBM) performance prediction is often a critical issue in the early stage of a tunnelling project, mainly due to the unpredictable nature of some important factors affecting the machine performance. In this regard, deterministic approaches are normally employed, providing results in terms of average values expected for the TBM performance. Stochastic approaches would offer improvement over deterministic methods, taking into account the parameter variability; however, their use is limited, since the level of information required is often not available. In this study, the data provided by the excavation of the Maddalena exploratory tunnel were used to predict the net and overall TBM performance for a 2.96 km section of the Mont Cenis base tunnel by using a stochastic approach. The preliminary design of the TBM cutterhead was carried out. A prediction model based on field penetration index, machine operating level and utilization factor was adopted. The variability of the parameters involved was analysed. A procedure to take into account the correlation between the input variables was described. The probability of occurrence of the outcomes was evaluated, and the total excavation time expected for the tunnel section analysed was calculated.

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

2010 ◽  
Vol 25 (4) ◽  
pp. 333-345 ◽  
Author(s):  
Jafar Khademi Hamidi ◽  
Kourosh Shahriar ◽  
Bahram Rezai ◽  
Jamal Rostami
Keyword(s):  
Rock Mass ◽  
Performance Prediction ◽  
Hard Rock ◽  
Rock Mass Rating ◽  
Hard Rock Tbm

TBM performance estimation using rock mass classifications

2002 ◽  
Vol 39 (6) ◽  
pp. 771-788 ◽  
Author(s):  
M Sapigni ◽  
M Berti ◽  
E Bethaz ◽  
A Busillo ◽  
G Cardone
Keyword(s):  
Rock Mass ◽  
Performance Estimation ◽  
Tbm Performance
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