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  4. Numerical methods for coupled population balance systems applied to the dynamical simulation of crystallization processes
 
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Numerical methods for coupled population balance systems applied to the dynamical simulation of crystallization processes

Publikationstyp
Book Part
Date Issued
2020-06-21
Sprache
English
Author(s)
Ahrens, Robin  
Lakdawala, Zahra  
Voigt, Andreas  
Wiedmeyer, Viktoria  
John, Volker  
Le Borne, Sabine  orcid-logo
Sundmacher, Kai  
Institut
Mathematik E-10  
TORE-URI
http://hdl.handle.net/11420/7166
Start Page
475
End Page
518
Citation
Dynamic Flowsheet Simulation of Solids Processes. Springer, Cham.: 475-518 (2020-06-21)
Publisher DOI
10.1007/978-3-030-45168-4_14
Scopus ID
2-s2.0-85089632937
Publisher
Springer, Cham.
Uni- and bi-variate crystallization processes are considered that are modeled with population balance systems (PBSs). Experimental results for uni-variate processes in a helically coiled flowtube crystallizer are presented.Asurvey on numerical methods for the simulation of uni-variate PBSs is provided with the emphasis on a coupled stochastic-deterministic method. In this method, the equations of the PBS from computational fluid dynamics are solved deterministically and the population balance equation is solved with a stochastic algorithm. With this method, simulations of a crystallization process in a fluidized bed crystallizer are performed that identify appropriate values for two parameters of the model such that considerably improved results are obtained than reported so far in the literature. For bi-variate processes, the identification of agglomeration kernels from experimental data is briefly discussed. Even for multi-variate processes, an efficient algorithm for evaluating the agglomeration term is presented that is based on the fast Fourier transform (FFT). The complexity of this algorithm is discussed as well as the number of moments that can be conserved.
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