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|Title: ||Combined quadrature method of moments and method of characteristics approach for efficient solution of population balance models for dynamic modeling and crystal size distribution control of crystallization processes|
|Authors: ||Aamir, Erum|
Nagy, Zoltan K.
Rielly, Chris D.
|Keywords: ||Population balance equation|
Quadrature method of moments
Method of characteristics
Crystal size distribution control
|Issue Date: ||2009|
|Publisher: ||© ACS Publications|
|Citation: ||AAMIR, E. ... et al, 2009. Combined quadrature method of moments and method of characteristics approach for efficient solution of population balance models for dynamic modeling and crystal size distribution control of crystallization processes. Industrial and Engineering Chemistry Research, 48 (18), pp. 8575-8584.|
|Abstract: ||The paper presents a novel methodology for the estimation of the shape of the crystal size
distribution (CSD) during a crystallization process. The approach, based on a combination of
the quadrature method of moments (QMOM) and the method of characteristics (MOCH),
provides a computationally efficient solution of the population balance equation (PBE) and
hence a fast prediction of the dynamic evolution of the CSD for an entire batch. Furthermore,
under the assumption that for supersaturation-controlled crystallization the main phenomenon is
growth, an analytical CSD estimator is derived for generic size-dependent growth kinetics.
These approaches are evaluated for the crystallization of potassium alum in water. The model
parameters are identified based on industrial experimental data, obtained using an efficient
implementation of supersaturation control. The proposed methods are able to predict and
reconstruct the dynamic evolution of the CSD during the batch. The QMOM-MOCH solution
approach is evaluated in a model based dynamic optimization study, which aims to obtain the
optimal temperature profiles required to achieve desired target CSDs. The technique can serve
as a soft sensor for predicting the CSD, or as a computationally efficient algorithm for off-line
design or on-line adaptation of operating policies based on knowledge of the full CSD data.|
|Description: ||This article is closed access. It was published in the journal, Industrial and Engineering Chemistry Research [© ACS Publications]: http://pubs.acs.org/page/iecred/about.html|
|Version: ||Closed access|
|Appears in Collections:||Closed Access (Chemical Engineering)|
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