Modeling and Simulation of Particulate Processes

A. Kienle 1,2, Prof. Dr.-Ing., S. Palis 2, Jun. Prof. Dr.-Ing.,
M. Mangold 1, Prof. Dr.-Ing., R. Durr 2, Dipl.-Ing.
1 Max Planck Institute for Dynamics of Complex Technical Systems
(Sandtorstr. 1, 39106 Magdeburg, Germany),
2 Otto von Guericke Universtat
(Universitatsplatz 2, 39106 Magdeburg, Germany)
(Tel. +49 391 67 58523, e-mail: Этот адрес электронной почты защищён от спам-ботов. У вас должен быть включен JavaScript для просмотра.)

АННОТАЦИЯ

Процессы в макрочастицах можно моделировать, используя популяционный баланс. Он представляет собой важный класс нелинейных дифференциальных уравнений в частных производных и широко применяеься в химической и биохимической инженерии. Основными проблемами при этом являются многомерные задачи, взаимосвязь с неидеальными полями течения и управление с обратными связями. В работе представленны возможные подходы к решению этих задач на примере различных процессов, таких как грануляция в
кипящем слое, кристализация и процессы производства вакцин от гриппа.

КЛЮЧЕВЫЕ СЛОВА:

partial differential equations, population balances, control, model reduction, proper orthogonal decomposition, direct quadrature method of moments.

СПИСОК ЛИТЕРАТУРЫ

1. Ramkrishna, D. (2000), Population balances: Theory and applications to particulate systems in engineering, Academic Press, New York, USA.
2. Deen, N.G., Van Sint Annaland, M., Van der Hoef, M.A. and Kuipers, J.A.M. (2007), Review of discrete particle modeling of fluidized beds, Chem. Engng. Sci., Vol. 62, pp. 28-44.
3. Heinrich, S., Peglow, M., Ihlow, M., Henneberg, M. and L. Mrl, L. (2002), Analysis of start-up process in continuous fluidized bed spray granulation by population balance modeling, Chem. Engng. Sci., Vol. 57, pp. 4369-4390.
4. Radichkov, R., Mller, T., Kienle, A., Heinrich, S., Peglow, M. and Mrl, L. (2006), A numerical bifurcation analysis of fluidized bed spray granulation with external classification, Chem. Engng. Proc., Vol. 45, pp. 826-837.
5. Palis, S. and Kienle, A. (2014), Discrepancy based control of particulate processes, J. Proc. Contr., Vol. 24, pp. 33-46.
6. Palis, S. and Kienle, A. Discrepancy based control of continuous fluidized bed spray granulation with internal product classification, Proc. 8th IFAC International Symposium on Advanced Control of Chemical Processes, Singapore, July 10-13, 2012, pp. 756-761.
7. Palis, S., Bck, A. and Kienle, A. (2013), Discrepancy based control of systems of population balances, Proc. 1st IFAC Workshop on Control of Systems Modeled by Partial Differential Equations, Paris, September 25-27, 2013, pp. 172-176.
8. Palis, S. and Kienle, A. (2012), Diskrepanz basierte Regelung der kontinuierlichen Flssigkristallisation, AT-Automatisierungstechnik, Vol. 60, pp. 145-154.
9. Krasnyk, M., Mangold, M., Ganesan, S. and L. Tobiska, L. (2012), Numerical reduction of a crystallizer model with internal and external coordinates by proper orthogonal decomposition, Chem. Engng. Sci., Vol. 70, pp. 77-86.
10. Krasnyk, M., Mangold, M. and Kienle, M. (2010), Extensions of the POD model reduction to multi-parameter domains, Chem. Engng. Sci., Vol. 65, pp. 6238-6246. 
11. Khlopov, D. andMangold, M. (2015), Automatic model reduction of linear population balance models by proper orthogonal decomposition, Proc. Vienna Conference on Mathematical Modeling, Vienna, February 18-20, DOI 10.1016/j.ifacol.2015.05.019, 2015.
12. Mangold, M., Feng, L.H., Khlopov, D., Palis, S., Benner, P., Binev, D. and Seidel-Morgenstern, A. (2015), Nonlinear model reduction of a continuous fluidized bed crystallizer, J. Comp. Appl. Math., Vol. 89, pp. 253-266.
13. Mangold, M., Khlopov, D., Danker, G., Palis, S., Sviatnyi, V. and Kienle, A. (2014), Development and nonlinear analysis of dynamic plant models in ProMoT/DIANA, Chemie-Ing.-Techn., Vol. 86, pp. 1-12.
14. Genzel, Y. and Reichl, U. (2009), Continuous cell lines as a production system for influenza vaccines, Expert Rev. Vaccines, Vol. 8, pp. 1681-1692.
15. Müller, T., Drr, R., Isken, B., Schulze-Horsel, J., Reichl, U. and Kienle, A. (2013), Distributed modeling of human influenza a virus-host cell interactions during vaccine production, Biotechnol. Bioengng., Vol. 110, pp. 2252-2266.
16. Dürr, R., Mller, T., Isken, B., Schulze-Horsel, J., Reichl, U. and Kienle, A. (2012), Distributed modeling and parameter estimation of influenza virus replication during vaccine production, Proc. Vienna Conference on Mathematical Modeling, Vienna, February 15-17, 2012.
17. Dürr, R. and Kienle, A. (2014), An efficient method for calculating the moments of multi- dimensional growth processes in population balance systems, Can. J. Chem. Eng., Vol. 92, pp. 2088-2097.
18. Dürr, R.,Mller, T. and Kienle, A. (2015), Efficient DQMOM for multivariate population balance equations and application to virus replication in cell cultures, Proc. Vienna Conference on Mathematical Modeling, Vienna, February 18-20, DOI 10.1016/j.ifacol.2015.05.045, 2015.
19. Haseltine, E.L., Yin, J. and Rawlings, J.B. (2005), Dynamics of viral infections: incorporating both the intracellular and extracellular levels, Comput. Chem. Engng., Vol. 29, pp. 675-686.

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