Building population balance model for fluidized bed melt granulation: lessons from kinetic theory of granular flow

Tan, H.S.; Goldschmidt, Mjv; Boerefijn, R.; Hounslow, Michael J.; Salman, Agba D.; Kuipers, J.A.M.

doi:10.1016/j.powtec.2004.04.030

Cited by 77 publications

(36 citation statements)

References 6 publications

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“…where , are the mass in kg of solid and liquid respectively in the granule, V is the compartment volume in m 3 and Q is flow rate to and from compartments in . n is the density function,…”

Section: Population Balance Modelingmentioning

confidence: 99%

“…In this paper the aggregation kernel by Tan et al [3] will be used. The derivation of the aggregation kernel [3] is based on the principles of kinetic theory of granular flow (KTGF) and the equi-partition of kinetic energy (EKE) kernel developed by Hounslow [4].…”

Section: Population Balance Modelingmentioning

confidence: 99%

“…The derivation of the aggregation kernel [3] is based on the principles of kinetic theory of granular flow (KTGF) and the equi-partition of kinetic energy (EKE) kernel developed by Hounslow [4]. The aggregation kernel can be seen in equation…”

Section: Population Balance Modelingmentioning

confidence: 99%

“…al. [3] has demonstrated how a growth kernel can be derived based on the kinetic theory of granular flow. This includes the local random particle motion as a time dependent part next to the more classical size dependent aggregation kernel developed by Hounslow [4].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model

et al. 2018

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In high shear granulation it has been pointed out that there is a need for meso-scale resolution and coupling between flow field information and the evolution of particle properties. In this article we develop a modelling framework that compartmentalizes the high shear granulation process based on process relevant parameters both in time and space. It is built up by a coupled flow field and population balance solver and is used to resolve and analyze the effects of meso-scales on the evolution of particle properties. A Diosna high shear mixer is modelled with micro crystalline cellulose powder as the granulation material. The analysis of the flow field solution and compartmentalization allows for a resolution of the stress and collision peak at the impeller blades. Different compartmentalizations were done showing the importance of resolving the impeller region, both for only aggregating systems and systems with breakage. An investigation on the time evolution of the flow field depending on the changing particle properties was also done, indicating the importance of resolving meso scale phenomena in time as well as space.

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“…where , are the mass in kg of solid and liquid respectively in the granule, V is the compartment volume in m 3 and Q is flow rate to and from compartments in . n is the density function,…”

Section: Population Balance Modelingmentioning

confidence: 99%

Section: Population Balance Modelingmentioning

confidence: 99%

Section: Population Balance Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model

et al. 2018

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“…While this model yielded valuable information when applied to PBM (Tan et al, 2004) its application to predicting the dynamics of granule-granule collision for various FBMG operating conditions was not pursued.…”

Section: Background and Motivations Of The Studymentioning

confidence: 99%

Time scale analysis for fluidized bed melt granulation I: Granule–granule and granule–droplet collision rates

Chua

Makkawi

Hounslow

2011

Chemical Engineering Science

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Fluidized Bed Spray Granulators (FBMG) are widely used in the process industry for particle size growth; a desirable feature in many products, such as granulated food and medical tablets.In this paper, the first in a series of four discussing the rate of various microscopic events occurring in FBMG, theoretical analysis coupled with CFD simulations have been used to predict granule-granule and droplet-granule collision time scales. The granule-granule collision time scale was derived from principles of Kinetic Theory of Granular Flow (KTGF). For the droplet-granule collisions, two limiting models were derived; one is for the case of fast droplet velocity, were the granule velocity is considerable lower than that of the droplet (ballistic model) and another for the case were the droplet is traveling with a velocity similar to the velocity of the granules. The hydrodynamic parameters used in the solution of the above models were obtained from the CFD predictions for a typical spray fluidized bed system. The granule-granule collision rate within an identified spray zone was found to fall approximately within the range of 10 -2 and 10 -3 s, while the droplet-granule collision was found to be much faster, however, slowing rapidly (exponentially) when moving away from the spray nozzle tip. Such information, together with the time scale analysis of droplet solidification and spreading, discussed in part II and III of this study, are useful for probability analysis of the various event occurring during a granulation process, which then lead to be better qualitative and, in part IV, quantitative prediction of the aggregation rate.

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Dynamic Multiscale Modeling – An Application to Granulation Processes

Ingram

2010

Process Systems Engineering

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Building population balance model for fluidized bed melt granulation: lessons from kinetic theory of granular flow

Cited by 77 publications

References 6 publications

Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model

Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model

Time scale analysis for fluidized bed melt granulation I: Granule–granule and granule–droplet collision rates

Dynamic Multiscale Modeling – An Application to Granulation Processes

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