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Low-order dynamic models for ideal multicomponent distillation processes using nonlinear wave propagation theory

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons86359

Kienle,  A.
Process Synthesis and Process Dynamics, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Zitation

Kienle, A. (2000). Low-order dynamic models for ideal multicomponent distillation processes using nonlinear wave propagation theory. Chemical Engineering Science, 55, 1817-1828. doi:10.1016/S0009-2509(99)00463-7.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-A24A-D
Zusammenfassung
A new approach to the development of low-order dynamic models for multicomponent distillation processes is presented. This approach makes direct use of well known spatio-temporal pattern formation phenomena also termed as nonlinear wave propagation. It takes into account the typical features of multicomponent systems, i.e. coexistence of different constant pattern waves within a single section of a distillation column and the resulting wave interactions. In a first step, constant molar holdups and flow rates, constant pressure and constant relative volatilities are assumed. Under these conditions a rigorous analytical treatment is possible and a comparably simple but sound and robust method for nonlinear model reduction is developed. The approach applies to packed as well as staged columns provided the number of column stages is sudfficiently large. Application is demonstrated for two different distillation processes with a three and a five component mixture, respectively. It is shown that the dynamic behaviour of the low-order modelis in good agreement with corresponding reference model for a large set of operating conditions. Finally, extensions of the present approach to processes with variable molar flow rates as well as variable volatilities are discussed. © Copyright 2007 Elsevier B.V., All rights reserved. [accessed 2014 March 31st]