Prediction of particle composition distribution after fragmentation of heterogeneous materials

Barbery, G.; Leroux, D.

doi:10.1016/0301-7516(88)90053-1

Cited by 45 publications

(25 citation statements)

References 11 publications

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“…Note that various types of 3D biphase structure model has been proposed: the Boolean model 6,15) , the Poisson mosaic [20][21][22] , and the Voronoi tessellation [20][21][22] . All of them provide more complex structure than the abovementioned method.…”

Section: Internal Structure Of Biphase Particlesmentioning

confidence: 99%

Effect of Particle Shape on the Stereological Bias of the Degree of Liberation of Biphase Particle Systems

2017

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It is well known that in sectional measurements of polished ore samples, the degree of liberation is overestimated by stereological bias. The stereological bias is affected by particle shape, but the effect of particle shape on the stereological bias has not been studied systematically. In this study, particles of various shapes were modeled using a geodesic grid, and the internal structures of the particles were randomly designed. The stereological bias of liberation was assessed quantitatively by comparing the computed sectional information and the original three-dimensional information. The following results were obtained: 1) the effect of aspect ratio on the stereological bias is less than 12% when comparing cases with α ranging from 1.0 to 2.0; 2) the effect of particle surface roughness on the stereological bias is smaller than 7.6% when comparing cases with surface roughness (the quotient of the surface area of the volume equivalent ellipsoid and the surface area of a particle) ranging from 0.833 to 0.996. It was also con rmed that the previously proposed stereological correction method is applicable to irregularly shaped particles because the estimation error of the degree of liberation dramatically dropped from 56.4%-64.4% without any correction to 1.16%-3.41% using the proposed method.

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Section: Internal Structure Of Biphase Particlesmentioning

confidence: 99%

Effect of Particle Shape on the Stereological Bias of the Degree of Liberation of Biphase Particle Systems

2017

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“…Small polyhedra composed of flats with random location and orientation were randomly grouped into phase A or B with respect to F v . These were termed Poisson polyhedra in a previous study [35,36]; however, Poisson mosaic, as defined by Gay et al [18], was used in the present study.…”

Section: Introductionmentioning

confidence: 98%

“…This model is able to produce more complicated phase shapes than the dispersed phase model, though a spherical core phase is commonly used [37,38]. Barbery used the Poisson tessellations generated by the Poisson mosaic model as primary grains, and called the resulting configuration Boolean scheme texture with Poisson polyhedra as primary grains [35,36]. The magnitude of stereological bias in Barbery's model is reported to be similar to that in the Poisson mosaic model [18].…”

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confidence: 99%

Comparison of Seven Texture Analysis Indices for Their Applicability to Stereological Correction of Mineral Liberation Assessment in Binary Particle Systems

2017

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An effective correction method for stereological bias is required because of the importance of accurate assessment of mineral liberation of ore particles. Stereological bias is error caused by the estimation of a three-dimensional liberation state based on two-dimensional sectional measurements. Recent studies have proposed a stereological correction method based on sectional particle texture analysis, which employs numerical particle models. However, the applicability of this method to unfamiliar particle systems, with different shape and texture characteristics from the numerical particle model, has not been thoroughly investigated. In this study, the viability of the method for examination of the internal structure and shape of unfamiliar particles, was assessed using four types of particle systems, based on combinations of two types of internal structures (Boolean and Voronoi) and two types of particle shapes (spherical and irregular). Seven different texture analysis indices were utilized for composition distribution correction with regard to each of the four types of particle systems. The results suggested that a model based on the angular second moment and/or entropy, employed by the spatial gray level dependence method, showed the greatest viability for assessment of unfamiliar particle internal structure and/or shape.

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“…And this is not surprising, since as Barbery and Leroux (1988) commented, it is a very difficult subject. A range of approaches in modelling have been employed and a number of these approaches are described below.…”

Section: Riza Marianomentioning

confidence: 94%

“…But, Barbery and Leroux (1988) stated that the information generated by mineral liberation models is better described by the term "Particle Composition Distribution Prediction", just as particle size distribution prediction would be considered a nonsense if researchers were only attempting to predict the relative proportion in the fine or the coarse size range.…”

Section: Riza Marianomentioning

confidence: 99%

Measurement and modelling of the liberation and distribution of minerals in comminuted ores

Mariano¹

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There is a need to develop a model to predict the liberation of minerals in breakage products as this is a key step in linking comminution and separation models in an integrated mineral processing simulator. Such a model would allow metallurgists to optimise grinding operations in response to changes in ore characteristics. This thesis aims to predict mineral liberation using a model based on random breakage of a measured texture, and to validate the model prediction against actual experimental breakage tests. A published, texture-based model of mineral liberation that uses the assumption of random breakage of the mineral texture to generate product particles called the JK Gaudin Random Liberation Model (JK-GRLM) (Evans et al. 2013) has been used as the basis of this study.In earlier empirical work a number of researchers (Berube and Marchand (1984), Manlapig et al. (1985), Wightman et al. (2008) and Vizcarra (2010)) observed the heuristic model that the degree of liberation in a given size fraction is the same regardless of where in the comminution circuit a sample is collected. This behaviour was observed for various ore types and was found to be independent of the mode of breakage. However, the published research does not explicitly consider the effect of amount of energy applied to break the ore on the distribution of the mineral across liberation and particle size classes.Two ore types were used in this study, namely ores from Kanowna Belle (KB) and Kennecott Utah Copper Corporation (KUCC). The original JK-GRLM was applied to simulate the product particle liberation distribution from breakage of the two ores. Experimental validation of the JK-GRLM was conducted by comparing the simulated and measured liberation distribution results. In this study, three different impact breakage energies were applied to samples of each ore to investigate whether the amount of breakage energy input affects the liberation behaviour of the ore. The particulate products of these three impact breakage energies were analysed using the MLA to measure the cross-sectional area liberation that was then compared to equivalent areal liberation data from the simulated results.Comparison of the simulated and measured results for the KB and KUCC ores showed that the simulated cross-sectional area particle composition distributions using the original JK-GRLM did not predict the measured values accurately. While non-random breakage of the ore was recognised as one possible cause of the differences between the simulated and measured liberation, it was ii postulated that another potential reason for the inaccurate predictions is the way in which texture is represented in the original JK-GRLM. Specifically the representation of texture using an average grain size distribution, cubic grains and random spatial distribution of the mineral grains to create the feed ore texture in the breakage simulation rather than in the actual spatial arrangement and grain shape of the measured ore. Therefore, the JK-GRLM was extended to assess the eff...

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Prediction of particle composition distribution after fragmentation of heterogeneous materials

Cited by 45 publications

References 11 publications

Effect of Particle Shape on the Stereological Bias of the Degree of Liberation of Biphase Particle Systems

Effect of Particle Shape on the Stereological Bias of the Degree of Liberation of Biphase Particle Systems

Comparison of Seven Texture Analysis Indices for Their Applicability to Stereological Correction of Mineral Liberation Assessment in Binary Particle Systems

Measurement and modelling of the liberation and distribution of minerals in comminuted ores

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