In the last decades, a huge number of studies on carbon dioxide removal have been presented in the literature. The non-equilibrium nature of the process involves an accurate definition of the parameters' correlations and of the model's assumptions. One of the most important assumptions when developing a process model is the definition of the number of discretization points. In this paper an alternative methodology has been presented for the definition of the number of stages of the absorption column in order to fit all the transport phenomena taking part in the carbon dioxide removal process. Then, it was developed a rigorous model of the absorption unit and finally implemented in Aspen Custom Modeler® environment to manage with a high level of complexity. The results obtained demonstrate that the number of stages is fundamental for the correct representation of the process and its incorrect evaluation could lead to huge errors in the prediction of the performance of the plant. © 2014 Elsevier B.V.
Modelling of an Amine Based CO2 absorption plant: An alternative approach through the identification of the number of stages
Deiana, P.
2014-01-01
Abstract
In the last decades, a huge number of studies on carbon dioxide removal have been presented in the literature. The non-equilibrium nature of the process involves an accurate definition of the parameters' correlations and of the model's assumptions. One of the most important assumptions when developing a process model is the definition of the number of discretization points. In this paper an alternative methodology has been presented for the definition of the number of stages of the absorption column in order to fit all the transport phenomena taking part in the carbon dioxide removal process. Then, it was developed a rigorous model of the absorption unit and finally implemented in Aspen Custom Modeler® environment to manage with a high level of complexity. The results obtained demonstrate that the number of stages is fundamental for the correct representation of the process and its incorrect evaluation could lead to huge errors in the prediction of the performance of the plant. © 2014 Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.