By R.P. King
Dr. R. Peter King covers the sector of quantitative modeling of mineral processing gear and using those types to simulate the particular habit of ore dressing and coal washing as they're configured to paintings in business perform. the fabric is gifted in a pedagogical variety that's really compatible for readers who desire to examine the big variety of modeling equipment that experience advanced during this box. The types range extensively from one unit style to a different. accordingly every one version is defined in a few detail.Wherever attainable version constitution is said to the underlying actual procedures that govern the behaviour of particulate fabric within the processing apparatus. Predictive types are emphasized all through in order that, whilst mixed, they are often used to simulate the operation of complicated mineral processing flowsheets. the improvement of profitable simulation options is a big goal of the paintings that's lined within the textual content. * Covers all features of modeling and simulation* presents all priceless instruments to place teh idea into perform* loose CD ROM incorporated
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Extra resources for Modeling and Simulation of Mineral Processing Systems
Example text
9. Eleven separate size fractions were analyzed grades pv(gv |D) in a population of particles when the distribution of linear grades Pᐉ(gᐉ|D) has been measured or calculated from a theoretical model. 75) where K is the 12 12 transformation kernel. Pᐉ is the vector of 12 measured cumulative linear grades and pv is the desired vector of fractional volumetric grades. 76) is useless because even very small errors in the measured distribution, which must always be present, are magnified by the inversion and swamp the true solution pv.
10. The importance of transforming the data is immediately apparent from these figures. The untransformed data do not reveal the true nature of the liberation distribution and cannot be used to analyze the behavior of individual particle types in any mineral processing operation. This should be borne in mind when experimental image analysis data is to be used for model calibration purposes. 11 Liberation distributions of 11 particle size fractions of a 2-component ore measured by image analysis.
3 (upper graph). This is an essential requirement for the description of mineral liberation distributions for different particle sizes. When the particle size is distinctly larger than the sizes of the mineral grains within the ore, most particles in the population exhibit a mineral grade close to the mean value for the ore as a whole and the distribution is bell-shaped. On the other hand when the particle size is distinctly smaller than the sizes of the mineral grains, the tendency for liberated and nearly liberated particles to appear is greatly enhanced and the beta distribution function reflects this tendency by exhibiting a strong U-shape.