2021
DOI: 10.17159/2411-9717/1401/2021
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Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Abstract: 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 … Show more

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Cited by 8 publications
(3 citation statements)
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“…Blast rounds for the same design (blast 1-1 and blast 1-2), blast 2-1 and 2-2, and blast 3-1 and blast 3-2 gave different results, indicating the effect of rock intrinsic properties. This shows that blasting results do not only depend on the initiation method but also on the intrinsic properties of the rock, as mentioned in several findings [42][43][44]. This finding also revealed that nonelectric detonation techniques performed poorly with low percentage optimum-size material, as specified by the company's primary crusher inlet size (350 mm by 420 mm).…”
Section: Discussionsupporting
confidence: 67%
“…Blast rounds for the same design (blast 1-1 and blast 1-2), blast 2-1 and 2-2, and blast 3-1 and blast 3-2 gave different results, indicating the effect of rock intrinsic properties. This shows that blasting results do not only depend on the initiation method but also on the intrinsic properties of the rock, as mentioned in several findings [42][43][44]. This finding also revealed that nonelectric detonation techniques performed poorly with low percentage optimum-size material, as specified by the company's primary crusher inlet size (350 mm by 420 mm).…”
Section: Discussionsupporting
confidence: 67%
“…These models include some early fragmentation models, first Kuz-Ram models [22], crush zone model (CZM) and the two-component mode l(TCM) [23][24][25], extended Kuz-Ram model [26] and Swebrec function [27]. Some other methods were also adopted to predict rock fragmentation by many studies, for example, statistical modelling approach [28], muck-pile model [29], KCO model [30], and deep learning approach [31].…”
Section: Introductionmentioning
confidence: 99%
“…The KuzRam fragmentation model was derived by Cunningham (1983Cunningham ( , 1987, from Rosin -Rammler (1933) and Kuznetsov (1973) equations to calculate the average size and the uniformity index. This model is an empirical relationship that evaluates blast fragmentation by incorporating blast design parameters, blast geometry, explosive characteristics, quantity of explosive used and rock factors [41][42][43]. Parameters of the KuzRam model: • uniformity index:…”
mentioning
confidence: 99%