On the use of sectional techniques for the solution of depolymerization population balances: Results on a discrete-continuous mesh

2020 ◽  
Vol 31 (7) ◽  
pp. 2669-2679 ◽  
Author(s):  
Firnaaz Ahamed ◽  
Mehakpreet Singh ◽  
Hyun-Seob Song ◽  
Pankaj Doshi ◽  
Chien Wei Ooi ◽  
...  
Keyword(s):  
Population Balances

Certain Problems with the Application of Stochastic Diffusion Processes for the Description of Chemical Engineering Phenomena. Diffusional Change of Solid Particle Size

1996 ◽  
Vol 61 (4) ◽  
pp. 536-563
Author(s):  
Vladimír Kudrna ◽  
Pavel Hasal
Keyword(s):  
Particle Size ◽  
Solid Particle ◽  
Chemical Engineering ◽  
Diffusion Processes ◽  
Granular Systems ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Diffusion Term ◽  
Population Balances ◽  
And Diffusion

To the description of changes of solid particle size in population, the application was proposed of stochastic differential equations and diffusion equations adequate to them making it possible to express the development of these populations in time. Particular relations were derived for some particle size distributions in flow and batch equipments. It was shown that it is expedient to complement the population balances often used for the description of granular systems by a "diffusion" term making it possible to express the effects of random influences in the growth process and/or particle diminution.

scholarly journals Data Mining Crystallization Kinetics

2020 ◽  
Author(s):  
Cameron Brown ◽  
Diego Maldonado ◽  
Antony Vassileiou ◽  
Blair Johnston ◽  
Alastair Florence
Keyword(s):  
Random Forest ◽  
Kinetic Parameters ◽  
Crystallization Kinetics ◽  
Balance Model ◽  
Forest Models ◽  
Vast Literature ◽  
Random Forest Models ◽  
Kinetic Expression ◽  
Population Balances ◽  
Different Sources

<p>Population balance model is a valuable modelling tool which facilitates the optimization and understanding of crystallization processes. However, in order to use this tool, it is necessary to have previous knowledge of the crystallization kinetics, specifically crystal growth and nucleation. The majority of approaches to achieve proper estimations of kinetic parameters required experimental data. Across time, a vast literature about the estimation of kinetic parameters and population balances have been published. Considering the availability of data, this work built a database with information on solute, solvent, kinetic expression, parameters, crystallization method and seeding. Correlations were assessed and clusters structures identified by hierarchical clustering analysis. The final database contains 336 data of kinetic parameters from 185 different sources. The data were analysed using kinetic parameters of the most common expressions. Subsequently, clusters were identified for each kinetic model. With these clusters, classification random forest models were made using solute descriptors, seeding, solvent, and crystallization methods as classifiers. Random forest models had an overall classification accuracy higher than 70% whereby they were useful to provide rough estimates of kinetic parameters, although these methods have some limitations.</p>

A comparative study of high resolution schemes for solving population balances in crystallization

2006 ◽  
Vol 30 (6-7) ◽  
pp. 1119-1131 ◽  
Author(s):  
S. Qamar ◽  
M.P. Elsner ◽  
I.A. Angelov ◽  
G. Warnecke ◽  
A. Seidel-Morgenstern
Keyword(s):  
High Resolution ◽  
Comparative Study ◽  
High Resolution Schemes ◽  
Population Balances
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