A Review on the Prediction and Assessment of Powder Factor in Blast Fragmentation

Authors

  • George Agyei Department of Mining Engineering, University of Mines and Technology, Tarkwa, GHANA.
  • M. O. Nkrumah Department of Mining Engineering, University of Mines and Technology, Tarkwa, GHANA.

Keywords:

powder factor, intact rock properties, post-blast conditions and comminution theory, artificial neural networks

Abstract

Powder factor can be defined as the quantity of explosives (kg) required to break a unit volume or tonne (t) of rock. The prospect of excavating rocks by blasting is characterized by a specific consumption of explosives. In the past decades, researchers have come up with several precise approaches to predict powder factor or specific charge in blast operations other than through trial blast. Research in this area has focused on the relationship between rock mass properties, blasting material and blasting geometry to establish the powder factor. Also, the interaction between specific energy and particle size embodied in the theory of comminution that is less dependent on local conditions has been studied. In this paper, the various methods for powder factor estimation based on empirical and comminution theory modelling, as well as machine learning approaches in both surface bench blasting and underground tunnel operations, have been reviewed. The influence of intact rock properties on powder factor selection and the influence of powder factor selection on post-blast conditions have also been discussed. Finally, the common challenges that have been encountered in powder factor estimations have been pointed out in this regard.

http://dx.doi.org/10.4314/njt.v40i2.13

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Published

2021-04-28

Issue

Section

Chemical, Industrial, Materials, Mechanical, Metallurgical, Petroleum & Production Engineering