2011
DOI: 10.1016/j.powtec.2011.02.009
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An attainable region analysis of the effect of ball size on milling

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Cited by 38 publications
(15 citation statements)
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“…The mechanistic approach includes the matrix model, which considers grinding as a series of breakage events and the kinetic model, namely the population balance model, which considers grinding as a continuous process. Other researchers focused their efforts on the advantages of the Attainable Region (AR) approach [10][11][12], while recently Shi and Xie used the t 10 procedure to simulate batch [13] and continuous [14] grinding in a ball mill.…”
Section: Introductionmentioning
confidence: 99%
“…The mechanistic approach includes the matrix model, which considers grinding as a series of breakage events and the kinetic model, namely the population balance model, which considers grinding as a continuous process. Other researchers focused their efforts on the advantages of the Attainable Region (AR) approach [10][11][12], while recently Shi and Xie used the t 10 procedure to simulate batch [13] and continuous [14] grinding in a ball mill.…”
Section: Introductionmentioning
confidence: 99%
“…To effectively apply this graphical analysis technique to optimise various operating conditions of comminution circuits and unlock its potential, several researchers have coupled it with the population balance model [7,9,19,20,22], with insightful information drawn from the work. The population balance model is a size-mass balance that takes into account the selection and breakage functions resulting in the full description of the grinding process.…”
Section: The Ar Application In Comminutionmentioning
confidence: 99%
“…They found that the AR could be used to determine optimal policies to reduce milling processing time. Katubilwa et al [9] also used the AR to analyse the effect of ball size on milling, based on the experimental data they had collected from milling coal. They confirmed the generally accepted trend that grinding balls of small diameter tended to promote the production of fine particles at a higher rate than can be achieved by large balls.…”
Section: Introductionmentioning
confidence: 99%
“…This approach owes its origins to the field of chemical reaction engineering where Hildebrandt and Glasser (1990) tested it in choosing optimal reactor configurations. Over the years, different researchers (Katubilwa et al 2011;Danha et al 2015;Hlabangana et al 2018) have applied this optimization method on their laboratory scale data with the aim of either minimizing an experimental manipulated variable or maximizing an associated process variable. Since one of the objectives of operating any process is to make profit, the AR technique assists in this regard by way of specifying optimal experimental parameters that will result in either a maximum or minimum condition of the objective function.…”
Section: The Attainable Region Approachmentioning
confidence: 99%