Oil Vapor recovery is a critical process in downstream chemical industries, in oil and gas industries and in environmental protection. For that purpose, highly-efficient absorbent materials for vapor recovery are in h...Oil Vapor recovery is a critical process in downstream chemical industries, in oil and gas industries and in environmental protection. For that purpose, highly-efficient absorbent materials for vapor recovery are in high demand and their associated adsorption kinetics is of great importance for their performance. As oil vapor consists of multiple components with different physical and chemical properties, modeling the overall adsorption kinetics of activated carbon for multi-component oil vapor is essentially valuable for industrial applications. In this work, we developed a comprehensive model of multi-component gas adsorption kinetics on activated carbon in a packed-bed reactor and numerically solved the model by the finite element method. The predictions from the model are all in the reasonable range indicating good validity of the model. Some dimensionless parameters are also derived to further investigate the prediction results.展开更多
文摘Oil Vapor recovery is a critical process in downstream chemical industries, in oil and gas industries and in environmental protection. For that purpose, highly-efficient absorbent materials for vapor recovery are in high demand and their associated adsorption kinetics is of great importance for their performance. As oil vapor consists of multiple components with different physical and chemical properties, modeling the overall adsorption kinetics of activated carbon for multi-component oil vapor is essentially valuable for industrial applications. In this work, we developed a comprehensive model of multi-component gas adsorption kinetics on activated carbon in a packed-bed reactor and numerically solved the model by the finite element method. The predictions from the model are all in the reasonable range indicating good validity of the model. Some dimensionless parameters are also derived to further investigate the prediction results.
