Mechanized tunnel boring method is over than fifty years old. Performance prediction is one of important categories in tunneling projects and is important in selection of excavation method and type of tunnel boring machine. In this paper penetration rate of Ghomrud conveyance tunnel TBM had predict with NTH model. The important advantage of this model is applying the effect of ground condition and rock mass properties. Calculations show that average penetration rate and average advance rate of machine must be 4.7 meter per hour and 20 meter per day respectively. Predictions have shown, with 28 workdays per month, excavation of this tunnel must be completed in 32 months. Maximum penetration rate of 5.04 meter per hour was predicted for foliated Jurassic sandstone, shale and slate layers and minimum penetration rate of 3.72 meter per hour was predicted for quartzite layers. Similarly maximum advance rate of 22.7 meter per day was predicted for foliated Jurassic sandstone, shale and slate layers and minimum advance rate of 11.5 meter per day was predicted for faulted zones. Therefore with comparison of TBM operation and predicted values it can be evaluated a relationship between real operation and result of applied model, for use in future excavations in tunnel root.
Ahmadi, M., Hemmati Shabani, A., & Foroughi, M. (2006). Prediction of hard rock TBM penetration rate with NTH model
(Case study Ghomrud conveyance tunnel). Journal of Mining Engineering, 1(1), 33-40.
MLA
M Ahmadi; A Hemmati Shabani; M Foroughi. "Prediction of hard rock TBM penetration rate with NTH model
(Case study Ghomrud conveyance tunnel)". Journal of Mining Engineering, 1, 1, 2006, 33-40.
HARVARD
Ahmadi, M., Hemmati Shabani, A., Foroughi, M. (2006). 'Prediction of hard rock TBM penetration rate with NTH model
(Case study Ghomrud conveyance tunnel)', Journal of Mining Engineering, 1(1), pp. 33-40.
VANCOUVER
Ahmadi, M., Hemmati Shabani, A., Foroughi, M. Prediction of hard rock TBM penetration rate with NTH model
(Case study Ghomrud conveyance tunnel). Journal of Mining Engineering, 2006; 1(1): 33-40.
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