Nonlinear optimization of gravity solids classification based on the feed and deck angles: A law of mass action approach

Tutkimustuotos: Lehtiartikkeli

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Nonlinear optimization of gravity solids classification based on the feed and deck angles : A law of mass action approach. / Rotich, Nicolus; Tuunila, Ritva; Elkamel, Ali; Louhi-Kultanen, Marjatta.

julkaisussa: Powder Technology, Vuosikerta 291, 01.04.2016, s. 140-146.

Tutkimustuotos: Lehtiartikkeli

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Bibtex - Lataa

@article{2577907a65144784b2bed0f618758f4d,
title = "Nonlinear optimization of gravity solids classification based on the feed and deck angles: A law of mass action approach",
abstract = "Deck screen design parameters e.g. material of construction, deck angle of inclination, the feed throughputs, and physicochemical properties of the particles, are critical factors to consider in solids classification. Two significant and easily manipulated parameters that greatly affect screen performance are the feed rate and design geometry configuration. In this work we apply statistical analysis of variance (ANOVA) and nonlinear least squares optimization with parameter estimation concepts, first, to assess the significance of the two factors and, second to formulate flow prediction models that optimize the feed rate and classification efficiency. Experiments were conducted on a prototype screen of 556.28cm2 effective area, (1380cm2 total area). For glass beads of sizes 0.75, 1, 2, and 3mm, with 16 feed batches of 10g to 160g, and six inclination angles 5, 10, 12.5, 15, 17.5, and 20°, a maximum efficiency of 66.7{\%} was achieved with a screen loading of 86.5g, and an inclination angle of 17.5°. These results were then subjected to nonlinear least squares optimization, which showed that a maximum efficiency of 93.2{\%} can be achieved at batch loading as low as 36g. There was a favorable performance at the range of angles 12.5≤θ≤17.5°, but poor performance outside this range. The screening efficiency did not respond significantly to changes in screen loading, although loading had a significant effect on the screening capacity. Confirmation tests conducted at selected optimum parameters achieved a maximum efficiency of 72{\%} (at 12.5° with 49.6g batch load), and a maximum rate of 27g/s at 17.5° with 104g.",
keywords = "Gravity-classification, Mineral particles, Modeling",
author = "Nicolus Rotich and Ritva Tuunila and Ali Elkamel and Marjatta Louhi-Kultanen",
year = "2016",
month = "4",
day = "1",
doi = "10.1016/j.powtec.2015.11.007",
language = "English",
volume = "291",
pages = "140--146",
journal = "Powder Technology",
issn = "0032-5910",
publisher = "Elsevier",

}

RIS - Lataa

TY - JOUR

T1 - Nonlinear optimization of gravity solids classification based on the feed and deck angles

T2 - A law of mass action approach

AU - Rotich, Nicolus

AU - Tuunila, Ritva

AU - Elkamel, Ali

AU - Louhi-Kultanen, Marjatta

PY - 2016/4/1

Y1 - 2016/4/1

N2 - Deck screen design parameters e.g. material of construction, deck angle of inclination, the feed throughputs, and physicochemical properties of the particles, are critical factors to consider in solids classification. Two significant and easily manipulated parameters that greatly affect screen performance are the feed rate and design geometry configuration. In this work we apply statistical analysis of variance (ANOVA) and nonlinear least squares optimization with parameter estimation concepts, first, to assess the significance of the two factors and, second to formulate flow prediction models that optimize the feed rate and classification efficiency. Experiments were conducted on a prototype screen of 556.28cm2 effective area, (1380cm2 total area). For glass beads of sizes 0.75, 1, 2, and 3mm, with 16 feed batches of 10g to 160g, and six inclination angles 5, 10, 12.5, 15, 17.5, and 20°, a maximum efficiency of 66.7% was achieved with a screen loading of 86.5g, and an inclination angle of 17.5°. These results were then subjected to nonlinear least squares optimization, which showed that a maximum efficiency of 93.2% can be achieved at batch loading as low as 36g. There was a favorable performance at the range of angles 12.5≤θ≤17.5°, but poor performance outside this range. The screening efficiency did not respond significantly to changes in screen loading, although loading had a significant effect on the screening capacity. Confirmation tests conducted at selected optimum parameters achieved a maximum efficiency of 72% (at 12.5° with 49.6g batch load), and a maximum rate of 27g/s at 17.5° with 104g.

AB - Deck screen design parameters e.g. material of construction, deck angle of inclination, the feed throughputs, and physicochemical properties of the particles, are critical factors to consider in solids classification. Two significant and easily manipulated parameters that greatly affect screen performance are the feed rate and design geometry configuration. In this work we apply statistical analysis of variance (ANOVA) and nonlinear least squares optimization with parameter estimation concepts, first, to assess the significance of the two factors and, second to formulate flow prediction models that optimize the feed rate and classification efficiency. Experiments were conducted on a prototype screen of 556.28cm2 effective area, (1380cm2 total area). For glass beads of sizes 0.75, 1, 2, and 3mm, with 16 feed batches of 10g to 160g, and six inclination angles 5, 10, 12.5, 15, 17.5, and 20°, a maximum efficiency of 66.7% was achieved with a screen loading of 86.5g, and an inclination angle of 17.5°. These results were then subjected to nonlinear least squares optimization, which showed that a maximum efficiency of 93.2% can be achieved at batch loading as low as 36g. There was a favorable performance at the range of angles 12.5≤θ≤17.5°, but poor performance outside this range. The screening efficiency did not respond significantly to changes in screen loading, although loading had a significant effect on the screening capacity. Confirmation tests conducted at selected optimum parameters achieved a maximum efficiency of 72% (at 12.5° with 49.6g batch load), and a maximum rate of 27g/s at 17.5° with 104g.

KW - Gravity-classification

KW - Mineral particles

KW - Modeling

UR - http://www.scopus.com/inward/record.url?scp=84951052778&partnerID=8YFLogxK

U2 - 10.1016/j.powtec.2015.11.007

DO - 10.1016/j.powtec.2015.11.007

M3 - Article

VL - 291

SP - 140

EP - 146

JO - Powder Technology

JF - Powder Technology

SN - 0032-5910

ER -

ID: 10770375