TBM performance prediction developing a hybrid ANFIS-PNN predictive model optimized by imperialism competitive algorithm

2021 ◽  
Author(s):  
Hooman Harandizadeh ◽  
Danial Jahed Armaghani ◽  
Panagiotis G. Asteris ◽  
Amir H. Gandomi
Keyword(s):  
Predictive Model ◽  
Performance Prediction ◽  
Tbm Performance ◽  
Competitive Algorithm ◽  
Imperialism Competitive Algorithm

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.

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