Field penetration index (FPI) is one of the representative key parameters to examine tunnel boring machine (TBM) performance. Lack accurate FPI prediction can be responsible for numerous disastrous incidents associated with rock mechanics and engineering. This study aims predict TBM performance (i.e. FPI) by an efficient improved adaptive neuro-fuzzy inference system (ANFIS) model. was done usi...

The aim of this work is to use Data Mining tools to develop models for the prediction of hard rock tunnel boring machine (TBM) penetration rate (ROP). A database published by Yagiz (2008) was used to develop these models. The parameters of the database were the uniaxial compressive strength (UCS), an index used to quantify the brittleness and toughness and denominated peak slope index (PSI), th...

one of the most important parameters used for determining the performance of tunnel boring machines (tbms) is their penetration rate. the parameters affecting the penetration rate can be divided in two categories. the first category is the controllable parameters such as the tbm technical characteristics, and type and geometry of the tunnel, and the second one is the uncontrollable parameters s...

Drill and blast is the most cost-effective excavation method for underground construction, however, vibration noise, induced by blasting, have been consistently reported as problems. Cut blasting has widely employed to reduce blast-induced problems during excavation. We propose that large hole boring using state-of-the-art MSP (Multi-setting smart-investigation of ground pre-large boring) machi...