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À propos de : A Mechanistic Approach To Characterize CoalHeterogeneity in Predicting High-TemperatureVolatile Matter Yields        

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  • A Mechanistic Approach To Characterize CoalHeterogeneity in Predicting High-TemperatureVolatile Matter Yields
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  • The reflectance distribution of coal (the reflectogram), which shows the heterogeneity of coal,can be represented by several reflectance bins. In this paper, in considering the heterogeneity ofcoal, coal is regarded as a mixture of particles. Each particle is characterized by reflectance andis treated as being homogeneous, without considering the intraparticle heterogeneity. The chemicalcompositions (volatile matter (VM), carbon content (C%), ratio of hydrogen to carbon (H/C)) of asingle particle have been estimated from previous works and are used to derive the 13C NMRparameters of this particle. These parameters are input into the chemical percolation devolatilization (CPD) model to predict the high-temperature VM yields of this particle. The total VMyields of the coal can be obtained by a summation of the results of all of the particles. In theexperimental portion, the sink−float technique has been used to separate a series of coals intodifferent maceral-rich fractions, which exhibit very different reflectance distributions. The high-temperature VM yields of these samples have been obtained from drop tube furnace pyrolysisexperiments at 1400 °C to validate the model. The results from pyrolysis experiments and thesingle-particle modeling approach show that, under high temperature, the inertinite-rich fractionproduces less VM than does the vitrinite-rich fraction of the same coal. The inertinite-rich fractionhas a lower Q factor, which is defined as the ratio of high-temperature VM yields and proximateVM, than its vitrinite counterpart. The high-temperature VM yields also have been estimatedfrom bulk properties of coal samples from the CPD model. These estimations do not agree withthe experimental data. The model could not be applied to those coals that showed abnormalreflectance features.
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