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Numerical approximations of a population balance model for coupled batch preferential crystallizers

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons86141

Angelov,  I.
Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86282

Elsner,  M. P.
Physical and Chemical Foundations of Process Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86477

Seidel-Morgenstern,  A.
Physical and Chemical Foundations of Process Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Zitation

Qamar, S., Angelov, I., Elsner, M. P., Ashfaq, A., Seidel-Morgenstern, A., & Warnecke, G. (2009). Numerical approximations of a population balance model for coupled batch preferential crystallizers. Applied numerical mathematics: transactions of IMACS, 59(3-4), 739-753. doi:10.1016/j.apnum.2008.03.033.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-9325-9
Zusammenfassung
This article is concerned with the numerical approximations of population balance equations for modeling coupled batch preferential crystallization processes. The current setup consists of two batch crystallizers interconnected with two fines dissolution pipes. The crystallization of both enantiomers is assumed to take place in separate crystallizers after seeding with their corresponding crystals. The withdrawn fines are assumed to be dissolved in the dissolution unit after heating. crystallizer, the crystallizer temperature before entering to the opposite crystallizer. Two types of numerical methods are proposed for the simulation of this process. The first method uses high resolution finite volume schemes, while the second method is the so-called method of characteristics. On the one hand, the finite volume schemes which were derived for general system in divergence form, are computationally efficient, give desired accuracy on coarse grids, and are robust. On the other hand, the method of characteristics is in general a powerful tool for solving growth processes, has capability to overcome numerical diffusion and dispersion, gives highly resolved solutions, as well as being computationally efficient. A numerical test problem with both isothermal and non-isothermal conditions is considered here. The numerical results show clear advantages of the proposed schemes. © 2008 IMACS Published by Elsevier B.V. [accessed October 27, 2008]