Modeling batch crystallization processes: Assumption verification and improvement of the parameter estimation quality through empirical experiment design

Kalbasenka, Alex N.; Huesman, Adrie E. M.; Kramer, Herman J. M.

doi:10.1016/j.ces.2011.06.049

Cited by 10 publications

(10 citation statements)

References 17 publications

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“…A number of previous CFD studies have focused on the modelling of turbulent free-surface flow using the Volume-of-Fluid (VoF) method in unbaffled vessels agitated by radial-flow impellers (for example, Haque et al 13 , Cartland Glover and Fitzpatrick 25 , Haque et al 26 , Yang et al 27 and Yang and Zhou 28 ) and in vessels with two beavertail baffles agitated by a RCI entering from the bottom, 29,30 and compared the predictions with the measurements of components of mean velocity and turbulence kinetic energy. In these studies using the RANS (Reynolds-averaged Navier-Stokes) approach, turbulence was represented using the standard k-, 13,25,26,2830 Shearstress transport (SST) 13,26 and Reynolds-stress transport (RST) 6,26,30 models. In more recent studies, detached-eddy simulation (DES) 27,28 and large-eddy simulation (LES) 28 approaches have also been used.…”

Section: Previous Studies and Present Contributionsmentioning

confidence: 99%

Digital Design of Batch Cooling Crystallization Processes: Computational Fluid Dynamics Methodology for Modeling Free-Surface Hydrodynamics in Agitated Crystallizers

Corzo

Yue

Mahmud

2020

Org. Process Res. Dev.

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A framework for the digital design of batch cooling crystallization processes is presented comprising three stages, which are based on different levels of process complexity, integrating crystallizer hydrodynamics with crystallization kinetics and consequently with expected crystal size distribution. In the first stage of the framework, a computational fluid dynamics methodology is developed to accurately assess hydrodynamics in a typical batch crystallizer configuration, comprising a 20 L scale dish-bottom vessel with a single beavertail baffle agitated by a retreat curve impeller, used in the pharmaceutical as well as in the fine chemical industries. The hydrodynamics of crystallizers with such configurations is characterized by vortex formation on the free liquid surface. It is therefore important to model the free surface using the Volume-of-Fluid (VoF) method. Comparison of the predicted mean velocity components with experimental measurements using laser Doppler anemometry reveals that improved predictions are obtained using a differential Reynolds-stress transport model for turbulence coupled with the VoF for modeling the gas-liquid interface compared with those using the Shear-stress transport model and with a flat liquid surface. This study demonstrates that an accurate treatment of the liquid free surface for capturing vortex formation is essential for reliable predictions of the crystallizer's flow field. While the vortex depth is predicted to increase with increasing impeller Reynolds number, the dependence of hydrodynamic macroparameters, including power number, impeller flow number, and secondary circulation flow number, on Reynolds number reveals that they are essentially constant within the turbulent regime but fluctuate when the flow is in the transitional and laminar regimes as fluid viscosity increases.

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Section: Previous Studies and Present Contributionsmentioning

confidence: 99%

Digital Design of Batch Cooling Crystallization Processes: Computational Fluid Dynamics Methodology for Modeling Free-Surface Hydrodynamics in Agitated Crystallizers

Corzo

Yue

Mahmud

2020

Org. Process Res. Dev.

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“… 40 These types of measurements have been used for parameter estimation in a 75 L DT crystallizer. 42 Examples of reliable solid fraction measurements have been obtained from an industrial batch crystallizer of 1100 L capacity by Kalbasenka 41 and used for parameter estimation and optimization purposes.…”

Section: Estimation Problem For Batch Seeded Flash Cooling Crystallizmentioning

confidence: 99%

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements

Porru

Özkan

2017

Ind. Eng. Chem. Res.

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This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements.

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“…The mechanistic framework describes this phenomenological behavior in detail. Hence, the capable of prediction of these models is more accurate for crystallization processes where secondary nucleation occurs (Kalbasenka et al, 2011).…”

Section: Average Crystal Diameter D(43)mentioning

confidence: 99%

“…The key assumption for this model is that the process must be dominated by secondary nucleation that appears in seeded crystallizers (Kalbasenka et al, 2011). The model describes the kinetics for nucleation, crystal growth and attrition in terms of the physical properties of the system.…”

Section: Mechanistic Kinetic Modelling Approachmentioning

confidence: 99%

“…In that model, a constant parameter related to the degree of primary nucleation heterogeneity is considered. Kalbasenka et al, (2011) made use of experimental data obtained from different batches to estimate the kinetic parameters and dismissed the assumption of invariability of the kinetic parameters throughout the process. Finally, Quintana et al, (2008) presented a first study on the analysis of two different approaches to modelling the crystallization kinetics based of an empirical power law type (TPL) equations and a mechanistic framework.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Empirical and Mechanistic Approaches for Modelling Cane Sugar Crystallization

Bolaños¹

2018

Rev. Mex. Ing. Quim.

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This study presents the kinetic modelling for cane sugar batch crystallization. The study is based on two approaches to describe the nucleation (homogeneous primary and secondary) and growth kinetics, and the birth and death rates of crystals: a) empirical models with equations of type power law (TPL) and b) mechanistic approach with thermodynamic equations. Both approaches, describing the phenomena of crystallization at the microscopic level (by solving population balance equation by method of lines), were validated using experimental data from a pilot-scale plant. From the results of both approaches and experimental validation, we conclude that the mechanistic approach best represents the dynamic behavior of cane sugar batch crystallization under different operational conditions than the empirical approach (TPL). Keywords: crystallization, modelling, kinetics, mechanistic and empirical approaches. ResumenEste estudio presenta el modelado cinético para la cristalización por lotes de azúcar de caña. El estudio se basa en dos enfoques para describir las cinéticas de nucleación (primaria homogénea y secundaria), de crecimiento y las tasas de nacimiento y muerte de cristales: a) modelos empíricos con ecuaciones de tipo ley de potencias (TLP) y b) enfoque mecanístico con ecuaciones termodinámicas. Ambos enfoques describen los fenómenos de cristalización a nivel microscópico (con la solución del balance de población por método de líneas) y fueron validados usando datos experimentales provenientes de una planta escala piloto. De los resultados de ambos enfoques y la validación experimental, se concluye que el enfoque mecanístico representa mejor los comportamientos dinámicos de la cristalización por lotes de azúcar de caña bajo diferentes condiciones operativas con respecto al enfoque empírico (TLP). Palabras clave: cristalización, modelado, enfoque mecanístico y empírico.

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Modeling batch crystallization processes: Assumption verification and improvement of the parameter estimation quality through empirical experiment design

Cited by 10 publications

References 17 publications

Digital Design of Batch Cooling Crystallization Processes: Computational Fluid Dynamics Methodology for Modeling Free-Surface Hydrodynamics in Agitated Crystallizers

Digital Design of Batch Cooling Crystallization Processes: Computational Fluid Dynamics Methodology for Modeling Free-Surface Hydrodynamics in Agitated Crystallizers

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements

A Study on Empirical and Mechanistic Approaches for Modelling Cane Sugar Crystallization

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