Development of new empirical models for performance estimation of a raise boring machine

Aydin Shaterpour-Mamaghani*, Hanifi Copur, Engin Dogan, Tayfun Erdogan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Raise boring machines (RBMs) are used for drilling/excavation of shafts and other inclined structures in mining and construction fields. Proper selection and accurate performance estimation of RBMs are two main parameters that affect the cost estimation and planning of the mining and construction projects. This paper aimed to suggest new empirical models for estimation of performance and operational parameters of RBMs in reaming operation by using simple (linear and non-linear) and multiple (linear and non-linear) regression methods. Balya lead-zinc underground mine was visited to investigate excavation of the ventilation shaft with a RBM. Length and diameter of the excavated ventilation shaft are 331.36 m and 2.44 m, respectively. Core samples obtained from the closest borehole to the fifth ventilation shaft in Balya lead-zinc underground mine were tested for defining some of the basic physical-mechanical properties. In addition, operational and performance parameters of the RBM were recorded/calculated during field studies. The results of field and laboratory studies were used in a statistical analysis to develop new empirical models for estimation of performance and operational parameters of the RBM. The results indicated that the uniaxial compressive strength might be used for estimation of rotational speed and consumed reamerhead torque. Moreover, Brazilian tensile strength with static elasticity modulus could be good estimators for field specific energy. However, accuracy and reliability of the proposed models should be improved by additional rock types and RBMs with different sizes and capacities.

Original languageEnglish
Pages (from-to)428-441
Number of pages14
JournalTunnelling and Underground Space Technology
Volume82
DOIs
Publication statusPublished - Dec 2018

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

  • Empirical models
  • Performance estimation
  • Physical-mechanical properties
  • Raise boring machine

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