• Tunnel and Underground Space
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• v.22 no.2
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• pp.144-156
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• 2012

This paper discusses the methods of estimating the punch penetration indices and data analysis punch penetration test to estimate the TBM normal force and penetration rate. In punch penetration test is known as a useful test to estimate penetration rates and normal force of TBMs directly with several slope indices indicated drill-ability and brittleness of rocks. However, the standard methods and indices for punch penetration test are not suggested yet. The main purpose of punch penetration test which is prediction of normal force of TBM disc cutter when cutters excavate rock mass. In this study, the punch penetration tests were performed for 6 representative Korean rock types and variety length and diameter of rock core specimens. Among slope indices were obtained from punch penetration test, PLI and MLI which is suggested in this study show high correlation with cutter force measured by full-scale cutting test. The results show that the predicted normal force of a single disc cutter and the experimental error was 10%. Based on these results, it is concluded that punch penetration test is reliable laboratory test for estimating thrust and penetration rates of TBM.

• Tunnel and Underground Space
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• v.13 no.6
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• pp.413-420
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• 2003

Modelling for performance prediction of mechanical excavation is discussed in this paper. Two of the most successful performance prediction models, namely theoretical based CSM model and empirical based NTH model, are discussed and compared. The basic principles of rock cutting with disc cutters, especially Constant Cross Section cutters, are discussed and a theoretical model developed is introduced to provide an estimate of disc cutting forces as a function of rock properties and the cutting geometry. General modelling logic for the performance prediction of mechanical excavation is introduced. CSM computer model developed and currently used at the Earth Mechanics Institute(EMI) of the Colorado School of Mines is discussed. Example of input and output of this model is illustrated for the typical operation by Tunnel Boring Machine(TBM).

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.501-513
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• 2020

Cutter cutting tests for the cutter placement in the cutter head are being conducted through various studies. Although the cutter spacing at the minimum specific energy is mainly reflected in the cutter head design, since the optimum cutter spacing at the same cutter penetration depth varies depending on the rock conditions, studies on deciding the optimum cutter spacing should be actively conducted. The machine learning techniques such as the decision tree-based regression model and the SVM regression model were applied to predict the optimum cutter spacing ratio for the nonlinear relationship between cutter penetration depth and cutter spacing. Since the decision tree-based methods are greatly influenced by the number of data, SVM regression predicted optimum cutter spacing ratio according to the penetration depth more accurately and it is judged that the SVM regression will be effectively used to decide the cutter spacing when designing the cutter head if a large amount of data of the optimum cutter spacing ratio according to the penetration depth is accumulated.