Empirical Performance Prediction for Raise Boring Machines Based on Rock Properties, Pilot Hole Drilling Data and Raise Inclination

Shaterpour Mamaghanı A., Çopur H.

ROCK MECHANICS AND ROCK ENGINEERING, vol.54, no.4, pp.1707-1730, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 54 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.1007/s00603-020-02355-1
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Compendex, Geobase, ICONDA Bibliographic, INSPEC, DIALNET, Civil Engineering Abstracts
  • Page Numbers: pp.1707-1730
  • Keywords: Performance prediction, Pilot hole drilling, Raise boring machines, Raise inclination, Reaming, Rock properties
  • Istanbul Technical University Affiliated: Yes


The basic aim of this study is to develop empirical models for predicting performances of pilot hole drilling and reaming for raise boring operations using rock properties and pilot hole drilling operational parameters for classified raise inclinations [vertical (90 degrees) and inclined (70 degrees)] that could be used in feasibility and operational stages of a project. Field study includes collecting performance and operational parameters including rotational speeds, tricone bit and reamer head torques, weight on bit (pushing force), net reaming thrust (pulling) force, unit penetration rate, and field-specific energy. Totally 21 different rocks are sampled in eight different sites to define physical and mechanical properties. The empirical models developed by performing multi-variable regression analyses for the vertical and inclined reaming and pilot hole drilling data groups indicate that static elasticity modulus, dynamic elasticity modulus, uniaxial compressive strength, Brazilian tensile strength, and rock quality designation are the most important intact rock and rock mass properties affecting performances of the vertical and inclined reaming and pilot hole drilling. This study should be continued to develop more generalized and reliable prediction models, especially by adding different reamer head diameters and raise inclinations to the database as predictive parameters.