Impact of Blast Design Parameters on Rock Fragmentation in Building Stone Quarries

Sharma, Astha; Mishra, A. K.; Choudhary, Bhanwar Singh; Meena, Rohit

doi:10.18520/cs/v116/i11/1861-1867

Cited by 7 publications

(3 citation statements)

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“…They include parameters over which the operator has control and those that the operator does not. The former include blast design parameters such as geometrical and explosive parameters (Sharma et al, 2019) whereas the latter depend on the inherent properties of the rock being blasted. The geometrical parameters that the mine operator can control during blasting are shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Mutinda

Alunda

Maina

et al. 2021

J. S. Afr. Inst. Min. Metall.

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SYNOPSIS Assessment of blast fragment size distribution is critical in mining operations because it is the initial step towards mineral extraction. Different empirical models and techniques are available for predicting and investigating the consequences of blasting, one of which is the Kuznetsov-Cunningham-Ouchterlony (KCO) model. In this paper we summarize the advances in the empirical models from inception until now, and explore the improvements that have been made so far with particular emphasis is on the most recent KCO model. Utilization of the model and the errors that arise between expected and the actual outcomes are analysed. The results indicate that the KCO model remains useful for predicting the blast fragmentation at limestone mine sites, despite the availability of other advanced prediction models. It is also a valuable instrument for pre-surveying the impact of varying certain parameters of a blast plan. Keywords: blasting, rock fragmentation, modelling, prediction.

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Section: Introductionmentioning

confidence: 99%

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Mutinda

Alunda

Maina

et al. 2021

J. S. Afr. Inst. Min. Metall.

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“…Blaster design factors such as burden, spacing, stemming, bench stiffness ratio, and powder factor all have a significant impact on the fragmentation that occurs after a blast [ 28 ]. By manipulating these factors, it is possible to achieve the most favorable fragmentation, resulting in mean fragment sizes that can vary between 50 % and 200 % [ 28 , 29 ]. Numerous articles have analyzed the relationship between controllable factors during an explosion and the subsequent rock fragmentation.…”

Section: Literature Reviewmentioning

confidence: 99%

Explosive utilization efficiency enhancement: An application of machine learning for powder factor prediction using critical rock characteristics

Olamide Taiwo,

Gebretsadik,

Abbas

et al. 2024

Heliyon

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“…The optimization procedure was then carried out with the remaining input parameters, to determine their values based on Equation ( 13). This was done because the remaining input parameters have been found to be the key blast design parameters that have the greatest influence of the outcome of every blasting operation (Sharma et al 2019). Thus, considering a combination of an average of 91 blast holes and an average distance of 739.99 m, the other input parameters were determined using the optimization algorithm under consideration.…”

Section: Optimization Analysismentioning

confidence: 99%

A hybrid paretosearch algorithm and goal attainment method for maximizing production and reducing blast-induced ground vibration: a blast design parameter selection approach

Arthur

Kaunda

2020

Mining Technology

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This study uses a hybrid paretosearch algorithm and goal attainment method to determine blast design parameters that will maximize production (total blasted volume) and minimize blast-induced ground vibration. Fifty-five (51) blast data collected at Quarry X in the Western US are used. A nonlinear and linear regression models are developed to serve as the objective function for the minimization of blast-induced ground vibration and maximization of production respectively. The blast design parameters are then determined using the hybrid optimization technique. The results obtained show that hole depths of 11.58 m, burden of 4.24 m, spacing of 4.88 m and stemming length of 3.61 m are the blast design parameter values that produce a minimum PPV within the interval of 0.51 and 38.1 mm/sec as stated in the Explosive regulation by the Colorado State Division of Oil and Public Safety for a total blast volume greater than 16,622 m 3 .

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Impact of Blast Design Parameters on Rock Fragmentation in Building Stone Quarries

Cited by 7 publications

References 0 publications

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Explosive utilization efficiency enhancement: An application of machine learning for powder factor prediction using critical rock characteristics

A hybrid paretosearch algorithm and goal attainment method for maximizing production and reducing blast-induced ground vibration: a blast design parameter selection approach

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