Quantifying mineral grain size distributions for process modelling using X-ray micro-tomography

Evans, Catherine L.; Wightman, Elaine M.; Yuan, Xiaoli

doi:10.1016/j.mineng.2015.03.026

Cited by 49 publications

(34 citation statements)

References 11 publications

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“…Principles of CT are described in detail in numerous papers [27,29,35]. The method consists in essence in weakening the power of the X-ray beam when passing through a certain volume of the material.…”

Section: X-ray Computed Tomography (Ct)mentioning

confidence: 99%

“…In recent years, new technologies such as the scanning electron microscope (SEM)-based Mineral Liberation Analysis (MLA) or Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN) made their way into the mineralogist's laboratories [25,26]. More recently, also Computer Tomography (CT) was applied for mineralogical analyses [27][28][29][30]. CT is a nondestructive technique that allows for the visualization of internal structures of objects based on their different X-ray density.…”

Section: Introductionmentioning

confidence: 99%

“…CT is a nondestructive technique that allows for the visualization of internal structures of objects based on their different X-ray density. Originally, the method was used mainly for medical purposes, but since the 1990s it has also been used in other applications, first in petroleum geology [31][32][33] and later in process mineralogy [34] and process technology [27,29,30,35].…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

et al. 2020

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Profound knowledge of the structure and texture of rocks and ores as well as the behavior of the materials under external loads is essential to further improvements in size reduction processes, particularly in terms of liberation size. New analytical methods such as computer tomography (CT) were adopted to improve the understanding of material characteristics in rocks and ores relevant to mineral processing, particular the crushing and grinding and the modelling/simulation thereof. Results obtained on the texture and structure of identical samples of rather different rocks and ores (copper ore, granodiorite, kimberlite) are compared by CT with quantitative results from traditional optical microscopy obtained by quantitative microstructural analysis (QMA). While the two approaches show a good agreement of the results in many areas, the measurements with the two different methods also exhibit remarkable differences in other areas, which are discussed further. In conclusion, both methods have their specific advantages starting from sample preparation to the accuracy of information obtained concerning certain parameters of mode and fabric. While sample preparation is faster with CT and information on special distribution of metal minerals is more reliable, the information on mode, grain size and clustering seem to be more precise with QMA. Based on the results, it can be concluded that both methods are comparable in many areas, but in in the field of spatial distribution, they are merely complementary.

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Section: X-ray Computed Tomography (Ct)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

et al. 2020

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“…mineral grain size distribution) is described in Evans et al (2015). A series of image processing steps are involved to obtain quantitative data.…”

Section: Chapter 3 Experimental Programmentioning

confidence: 99%

“…In the study of Evans et al (2015) on KB ore, in comparison with MLA analyses of the particles the pyrite, carbonates and silicates phases can be distinguished visually in the greyscale image. The example of the classified mineral phases that can be seen in the KB ore measured using X-ray tomography is shown in Figure 3.20.…”

Section: Quantifying the Textural Characteristics From The Tomographymentioning

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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Application of micro‐CT to resolve textural properties and assess primary sedimentary structures of deep‐marine sandstones

Cornard,

Degenhart,

Tropper

et al. 2023

The Depositional Record

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Over the past decade, there has been growing interest in the sedimentological community to use micro X‐ray computed tomography to analyse microfacies in sediment cores. However, little attention has been paid to the application of micro‐computed tomography in lithified deposits, even though this can allow their texture to be characterised in three dimensions, providing key information about sedimentary structures. A novel application of micro‐computed tomography in lithified sediment‐gravity flow deposits is presented with the objective of characterising their internal 3D sedimentary structures. This technique is applied to three deep‐marine sandstones showing different compositional properties: Cretaceous Gosau Group (Austria), Eocene Hecho Group (Spain) and the Oligocene Annot Formation (France). From micro‐computed tomography data the size of particles and their distribution throughout the sample is reconstructed in 3D permitting a better visualisation of sedimentary textures. Particle distributions computed from micro‐computed tomography are similar to those computed from thin section image analysis, corroborating the reliability of the micro‐computed tomography to evaluate grain‐size trends. Micro‐computed tomography is complemented with micro‐X‐ray fluorescence and thin section petrographic analyses. In cases where mineral composition or grain size are homogeneous or matrix and grains have similar mineral composition, sedimentary structures do not appear visible from micro‐X‐ray fluorescence or thin section analyses. By separating particles based on their computed tomography density, it is possible to isolate the coarsest fraction, highlighting the sedimentary structures. This study demonstrates (i) the potential of micro‐computed tomography in analyses of sedimentary structures from outcrop data and (ii) the importance of the mineralogical composition and degree of grain sorting in assessing the origin of structureless deposits. Considering the importance of visualising sedimentary structures when interpreting depositional processes, micro‐computed tomography is a new and reliable tool to assess the physical properties of sandstones and to analyse their internal 3D sedimentary structures.

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Quantifying mineral grain size distributions for process modelling using X-ray micro-tomography

Cited by 49 publications

References 11 publications

Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

Quantitative Microstructural Analysis and X-ray Computed Tomography of Ores and Rocks—Comparison of Results

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

Application of micro‐CT to resolve textural properties and assess primary sedimentary structures of deep‐marine sandstones

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