SK
S. Klerkx
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2 records found
1
Journal article
(2026)
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Sean Klerkx, Masoud Soleymani Shishvan, Amin Moniri-Morad, Javad Sattarvand
Drillhole location deviations can disrupt energy distribution within mining benches, leading to uneven fragmentation and reduced operational efficiency. This study presents an optimisation approach that compensates for drilling inaccuracies to achieve more uniform energy input. The method involves discretizing the bench into a block model to estimate localised energy distribution and constructing a mathematical model to minimise discrepancies between the planned and actual energy delivery. A Tabu Search algorithm is used to solve the model. Case studies demonstrated improvements in the objective function, ranging from 0.53%–1.54% overall, and 2.14%–3.94% within the zones most affected by deviation.
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Drillhole location deviations can disrupt energy distribution within mining benches, leading to uneven fragmentation and reduced operational efficiency. This study presents an optimisation approach that compensates for drilling inaccuracies to achieve more uniform energy input. The method involves discretizing the bench into a block model to estimate localised energy distribution and constructing a mathematical model to minimise discrepancies between the planned and actual energy delivery. A Tabu Search algorithm is used to solve the model. Case studies demonstrated improvements in the objective function, ranging from 0.53%–1.54% overall, and 2.14%–3.94% within the zones most affected by deviation.
The inaccurately drilled blastholes from the planned locations cause changes in the spatial distribution of explosive energy; some areas of the blast may receive a surplus of explosive energy, while others see a reduction. This results in less uniform fragmentation, reduces the efficiency of mining operations and increases costs. Additionally, it can lead to slope stability issues, flyrock, and uneven benches. To mitigate these problems, this study attempts to reduce differences in the explosive energy distribution (EED) through an optimization approach that adjusts the height of explosive columns in blastholes. Two optimization algorithms, the Genetic Algorithm (GA) and Tabu Search (TS), are tested. The latter is preferred for its local search neighbourhood strategy that gives superior computation times. Applications on different blast patterns result in improvements of 0.53-1.54%, or 2.14–3.94% when only the affected blocks are considered.
...
The inaccurately drilled blastholes from the planned locations cause changes in the spatial distribution of explosive energy; some areas of the blast may receive a surplus of explosive energy, while others see a reduction. This results in less uniform fragmentation, reduces the efficiency of mining operations and increases costs. Additionally, it can lead to slope stability issues, flyrock, and uneven benches. To mitigate these problems, this study attempts to reduce differences in the explosive energy distribution (EED) through an optimization approach that adjusts the height of explosive columns in blastholes. Two optimization algorithms, the Genetic Algorithm (GA) and Tabu Search (TS), are tested. The latter is preferred for its local search neighbourhood strategy that gives superior computation times. Applications on different blast patterns result in improvements of 0.53-1.54%, or 2.14–3.94% when only the affected blocks are considered.