Fine grinding size distribution analysis using the Swrebec function

Osorio, Adriana; Menéndez-Aguado, Juan M.; Bustamante, Oswaldo; Restrepo, Gloria

doi:10.1016/j.powtec.2014.03.036

Cited by 18 publications

(11 citation statements)

References 5 publications

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“…The parameters are the maximum size x max , the size with 50% cumulative undersize x 50 and the undulation parameter b. In the work of Osorio et al [34], the Swebrec model was evaluated in the wet grinding process of quartz ore, obtaining an excellent fitting adjustment. Menéndez-Aguado et al [35] presented the Swebrec distribution to fit sediment particle size distribution with a high correlation between experimental and model data.…”

Section: Methodsmentioning

confidence: 99%

Particle Size Distribution Models for Metallurgical Coke Grinding Products

Colorado-Arango

Menéndez-Aguado

Correa

2021

Metals

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Six different particle size distribution (Gates–Gaudin–Schuhmann (GGS), Rosin–Rammler (RR), Lognormal, Normal, Gamma, and Swebrec) models were compared under different metallurgical coke grinding conditions (ball size and grinding time). Adjusted R2, Akaike information criterion (AIC), and the root mean of square error (RMSE) were employed as comparison criteria. Swebrec and RR presented superior comparison criteria with the higher goodness-of-fit and the lower AIC and RMSE, containing the minimum variance values among data. The worst model fitting was GGS, with the poorest comparison criteria and a wider results variation. The undulation Swebrec parameter was ball size and grinding time-dependent, considering greater b values (b > 3) at longer grinding times. The RR α parameter does not exhibit a defined tendency related to grinding conditions, while the k parameter presents smaller values at longer grinding times. Both models depend on metallurgical coke grinding conditions and are hence an indication of the grinding behaviour. Finally, oversize and ultrafine particles are found with ball sizes of 4.0 cm according to grinding time. The ball size of 2.54 cm shows slight changes in particle median diameter over time, while 3.0 cm ball size requires more grinding time to reduce metallurgical coke particles.

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Section: Methodsmentioning

confidence: 99%

Particle Size Distribution Models for Metallurgical Coke Grinding Products

Colorado-Arango

Menéndez-Aguado

Correa

2021

Metals

Self Cite

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“…In addition, fractal geometry which is based on the idea of self-similarity is also widely used for describing various complex natural phenomena, including particle size distribution [41,42]. Other studies have used the Swrebec distribution model as an alternative to traditional distributions because of its goodness-of-fit in both coarse and fine size ranges [43,44]. The Rosin-Rammler distribution that was used in the present study is expressed by Equation (3),…”

Section: Mathematical Models For the Simulation Of Psdmentioning

confidence: 99%

Grinding Kinetics of Slag and Effect of Final Particle Size on the Compressive Strength of Alkali Activated Materials

et al. 2019

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This study aims to model grinding of a Polish ferronickel slag and evaluate the particle size distributions (PSDs) of the products obtained after different grinding times. Then, selected products were alkali activated in order to investigate the effect of particle size on the compressive strength of the produced alkali activated materials (AAMs). Other parameters affecting alkali activation, i.e., temperature, curing, and ageing time were also examined. Among the different mathematical models used to simulate the particle size distribution, Rosin-Rammler (RR) was found to be the most suitable. When piecewise regression analysis was applied to experimental data it was found that the particle size distribution of the slag products exhibits multifractal character. In addition, grinding of slag exhibits non-first-order behavior and the reduction rate of each size is time dependent. The grinding rate and consequently the grinding efficiency increases when the particle size increases, but drops sharply near zero after prolonged grinding periods. Regarding alkali activation, it is deduced that among the parameters studied, particle size (and the respective specific surface area) of the raw slag product and curing temperature have the most noticeable impact on the compressive strength of the produced AAMs.

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“…distribution model as an alternative to traditional distributions because of its goodness-of-fit in both coarse and fine size range [42,43]. The Rosin-Rammler distribution that was used in the present study is expressed by Equation 3,…”

Section: Mathematical Models For the Simulation Of Psdmentioning

confidence: 99%

Grinding Kinetics of Slag and Effect of Final Particle Size on the Compressive Strength of Alkali Activated Materials

Petrakis¹,

Karmali²,

Bartzas³

et al. 2019

Preprint

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This study aims to model grinding of a Polish slag and evaluate the particle size distributions of the products obtained after different grinding times. Then, selected products were alkali activated in order to investigate the effect of particle size on the compressive strength of the produced alkali activated materials (AAMs). Other parameters affecting alkali activation, i.e. temperature, curing and ageing time were also examined. Among the different mathematical models used to simulate the particle size distribution, Rosin-Rammler (RR) was found to be the most suitable. When piecewise regression analysis was applied to experimental data it was found that the particle size distribution of the slag products exhibits multi fractal character. In addition, grinding of slag exhibits non-first-order behavior and the reduction rate of each size is time dependent. The grinding rate and consequently the grinding efficiency increases when the particle size increases, but drops sharply near zero after prolonged grinding periods. Regarding alkali activation, it is deduced that among the parameters studied, particle size (and the respective specific surface area) of the raw slag product and curing temperature have the most noticeable impact on the compressive strength of the produced AAMs.

show abstract

Fine grinding size distribution analysis using the Swrebec function

Cited by 18 publications

References 5 publications

Particle Size Distribution Models for Metallurgical Coke Grinding Products

Particle Size Distribution Models for Metallurgical Coke Grinding Products

Grinding Kinetics of Slag and Effect of Final Particle Size on the Compressive Strength of Alkali Activated Materials

Grinding Kinetics of Slag and Effect of Final Particle Size on the Compressive Strength of Alkali Activated Materials

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