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Simplified local-density modeling of pure and multi-component gas adsorption on dry and wet coals.

机译:干煤和湿煤上纯和多组分气体吸附的简化局部密度模型。

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The Simplified Local-Density/Peng-Robinson (SLD-PR) adsorption model was utilized to generalize pure and mixed-gas adsorption predictions of methane (CH4), nitrogen (N2) and carbon dioxide (CO2) on ten coals (dry Argonne premium and wet OSU coals).;The SLD-PR model parameters were regressed to obtain representations for each coal and were then generalized in terms of adsorbent characteristics and methane excess adsorption at 400 psia. These generalized model parameters predicted the pure-gas adsorption on these coals with an overall weighted absolute average deviation (WAAD) of 1.1. Further, these pure fluid generalized parameters predicted most of the mixture adsorption on wet OSU coals within three times the experimental uncertainties.;Equation-of-State binary interaction parameters (BIPs) were incorporated to improve mixture adsorption predictions. The BIPs were regressed and generalized in terms of coal characteristics which resulted in the mixture adsorption predictions were improved to within twice the experimental uncertainties on average.
机译:利用简化的局部密度/ Peng-Robinson(SLD-PR)吸附模型,对十种煤(干阿贡精油)中甲烷(CH4),氮气(N2)和二氧化碳(CO2)的纯气体和混合气体吸附预测进行了概括回归SLD-PR模型参数以获得每种煤的表示形式,然后根据400 psia的吸附剂特性和甲烷过量吸附进行概括。这些广义模型参数预测了纯煤在这些煤上的吸附,总加权绝对平均偏差(WAAD)为1.1。此外,这些纯流体广义参数预测了大多数混合物在湿OSU煤上的吸附,其不确定度是实验不确定性的三倍。引入了状态方程二元相互作用参数(BIP)以改善混合物的吸附预测。根据煤的特性对BIPs进行了回归和归纳,导致混合物吸附预测值提高到平均实验不确定性的两倍之内。

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