Open Access

Improvement of Blast-induced Fragmentation Using Artificial Neural Network and BlastFrag© Optimizer Software

Blessing Olamide Taiwo
Blessing Olamide Taiwo
 and 
Babatunde Adebayo
Babatunde Adebayo
   | Sep 04, 2023
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Article Category: Original Scientific Article
Published Online: Sep 04, 2023
Page range: 47 - 59
Received: Oct 16, 2021
Accepted: Jan 11, 2022
DOI: https://doi.org/10.2478/rmzmag-2021-0010
Keywords
© 2022 Blessing Olamide Taiwo et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1

a) Geological map of Akoko Edo, showing case study area. b) Quarry face showing the sampling points marked with red circles. c) Quarry scheme of the drilling patterns.
a) Geological map of Akoko Edo, showing case study area. b) Quarry face showing the sampling points marked with red circles. c) Quarry scheme of the drilling patterns.

Figure 2

a) Blast image with 1 m by 1 m scaling frame and image scale, b) Delineated image with scale, and c) WipFrag result particle size distribution curve.
a) Blast image with 1 m by 1 m scaling frame and image scale, b) Delineated image with scale, and c) WipFrag result particle size distribution curve.

Figure 3

ANN connection network structure.
ANN connection network structure.

Figure 4

a) Levenberg-Marquardt models architecture and network regression curves, b) Bayesian regularization algorithm models architecture and network regression curves.
a) Levenberg-Marquardt models architecture and network regression curves, b) Bayesian regularization algorithm models architecture and network regression curves.

Figure 5

Relationship between predicted and measured a) percent oversize; b) percent undersize; c) mean size using ANN.
Relationship between predicted and measured a) percent oversize; b) percent undersize; c) mean size using ANN.

Figure 6

Comparison of the ANN simulation input with the software (a) %oversize; (b) %undersize; (c) mean size.
Comparison of the ANN simulation input with the software (a) %oversize; (b) %undersize; (c) mean size.

Figure 7

BlastFrag optimizer user interface.
BlastFrag optimizer user interface.

Blast design parameters for the quarry

Parameter Pit 1 Pit 2 Pit 3 Pit 4 Pit 5 Pit 6
Burden(m) 0.7 0.82 0.85 0.85 0.7 0.85
Spacing (m) 0.85 0.96 1.10 1.1 1.0 1.1
Hole depth (m) 1.25 1.3 1.35 1.3 1.35 1.35
Drill pattern staggered Staggered staggered staggered staggered square
Hole diameter (m) 0.04 0.04 0.04 0.04 0.04 0.04
Drill hole depth (m) 1.25 1.3 1.35 1.3 1.35 1.3
Stemming (m) 0.65 0.7 0.66 0.66 0.7 0.6
Drilling accuracy 0.054 0.054 0.054 0.054 0.054 0.054
Charge length (m) 0.65-0.7 0.67-0.76 0.6-0.76 0.6-0.7 0.6-0.78 0.6-0.8
Charge weight (kg) 0.96-1.02 0.80-0.95 0.9-1.14 0.8-0.85 0.6-0.8 0.65-0.85
Crusher gap (m) 0.28 0.28 0.28 0.28 0.28 0.28

Blasting output statistics and cost per hole blast

Blast parameters Blast before ANN model design Blast with BlastFrag model design
Diameter (mm) 0.04 0.04
Burden (m) 0.7 0.8
Spacing (m) 1.1 1.2
Drill hole length (m) 1.3 1.4
Rock average specific gravity 2.8 2.8
Production per hole blasted (Tonnes) 2.59 3.76
Percent oversize 68.4% 27.83%
Percent undersize 50% 72.17%
Mean size (mm) 418.0 101.6
Profit from blast per hole (Naira) 10,360 15,040
Cost per hole charge (Naira) 1000 950

Explosive data and information about the quarry

Parameter Pit 1 Pit 2 Pit 3 Pit 4 Pit 5 Pit 6
Charge length (m) 0.65-0.7 0.67-0.76 0.6-0.76 0.6-0.7 0.6-0.78 0.6-0.8
Type of explosive Dynogel Dynogel Dynogel Dynogel Dynogel Dynogel
Density of ANFO (kg/m3) 820 820 820 820 820 820
Density of explosive (kg/m3) 1190 1190 1190 1190 1190 1190
Powder factor (kg/m3) 0.8-0.0.9 0.0.7-0.8 0.5-0.6 0.5-0.86 0.6-1.0 0.7-0.85
RWS 1.45 1.45 1.45 1.45 1.45 1.45
VOD (m/s) 5250 5250 5250 5250 5250 5250
Explosive strength 1.45 1.45 1.45 1.45 1.45 1.45

Computed RMSE and R2 for comparing ANN and modified KUZ-RAM models

Models Blasting Parameters R2 RMSE
ANN model Oversize (%) 0.927 1.09
Undersize (%) 0.866 1.14
Mean-size (mm) 0.930 3.46
Modified Oversize (%) 0.111 4.48
Kuz-Ram model Undersize (%) 0.073 4.58
Mean-size (mm) 0.157 14.03

Summary of the rock characterization of Golden Girl Quarry

Parameter Pit 1 Pit 2 Pit 3 Pit 4 Pit 5 Pit 6
Uniaxial compressive strength (MPa) 173.75 178.75 171.25 167.75 168.75 186.25
Joint spacing (m) 0.76 0.26 0.64 0.20 0.32 0.28
Dip direction (0) 298 312 260 034 312 064
Dip angle (0) 58 30 74 42 48 78
Rock density (kg/m3) 2804 2790 2886 2760 2860 2800
Young modulus (GPa) 60 75 75 68.5 60 75

Input parameters and their symbols

Parameter Symbol Range Parameter Symbol Range
UCs U 160-186.25Mpa % oversize Q 23.3%-70%
Density M 2800-2886 kg/m3 % undersize Y 32%-72.1%
Spacing S 0.8-1.1 m Mean size (mm) V 220%--480 mm
Hole depth D 1.25-1.35 m
Stemming length T 0.6-0.7 m
Hole diameter H 0.04 m
Powder factor K 0.6-1.0 kg/m3
Charge weight W 0.6-0.96 kg
Burden B 0.7-0.85 m
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