Global statistical predictor model for characteristic adsorption energy of organic vapors-solid interaction: use in dynamic process simulation.

作者: Shivaji G. Ramalingam , Lomig Hamon , Pascaline Pré , Sylvain Giraudet , Laurence Le Coq

DOI: 10.1016/J.JCIS.2012.03.068

关键词: Process simulationRange (statistics)ThermodynamicsData pointEquilibrium pointChemistryLinear regressionAdsorptionFreundlich equationCharacteristic energy

摘要: Adsorption of Volatile Organic Compounds (VOCs) is one the best remediation techniques for controlling industrial air pollution. In this paper, a quantitative predictor model characteristic adsorption energy (E) Dubinin-Radushkevich (DR) isotherm has been established with R(2) value 0.94. A by using Multiple Linear Regression (MLR) analysis in statistical package MINITAB. The experimental was computed modeling equilibrium data (which contain 120 isotherms involving five VOCs and eight activated carbons at 293, 313, 333, 353 K) Gauss-Newton method R-STAT. MLR validated points, it will be implemented dynamic simulation PROSIM. By implementing model, predicts an enormous range 1200 coefficients DR different temperatures such as 353K (each 10 points changing concentration) just simple without any experiments.

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