Theoretical Study of Granulation Kinetics in a Batch Fluidized Bed

Mitrofanov, A.V.; Mizonov, Vadim E.; Tannous, Kátia; Ovchinnikov, L. N.

doi:10.6060/tcct.2017605.5611

Cited by 2 publications

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“…Later on, this approach was developed to the case of particles with time-varying properties [18]. Its application to the layering granulation is described in [19]. However, only a binary mixture of particles was examined in this work: the primary particles and completely granulated particles.…”

Section: Introductionmentioning

confidence: 99%

“…The objective of the present study is to generalize the approach described in [19] to the case of gradual growth of particles and to perform experiments to compare the computational and experimental results. THEORY Fig.…”

Section: Introductionmentioning

confidence: 99%

“…They will transit to the corresponding cell of the neighboring fraction B. Now it is necessary to calculate what volume of particles will appear in B and will be lost in A [19].…”

Section: Introductionmentioning

confidence: 99%

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Computational and Experimental Study of Granulation in Fluidized Bed Reactor

Mizonov

Mitrofanov

Tannous

et al. 2019

IVKKT

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The objective of the study is to build a simple but informative model to describe the kinetics of layering granulation in a batch fluidized bed reactor. A cell model based on the theory of Markov chains to describe this kinetics is proposed. Several parallel chains of perfectly mixed cell according to the number of size fractions, which are under observation, were introduced. The vectors of particles volume content in the cells describe the state of the process. Evolution of the state is conditioned by particles transition from the cells of one chain to another due to their size enlargement during granulation and by particles migration along the chains due to their interaction with fluidizing gas upstream flow. The process is observed in a discrete moments of time. It is supposed that the volume of binding solution coming into a cell of a chain during one time step interacts only with the particles that can enlarge their size to transit to the cell of the next larger size fraction. The migration of the particles of a size fraction along its chain is controlled by the matrix of transition probabilities, which is different for each size fraction and depends on the total particles concentration. The model allows qualitative estimating of influence of the process parameters on the granulation kinetics. In order to validate the model, the experimental study of ammonium sulphate granulation in the lab scale fluidized bed reactor was carried out. The comparison of theoretical and experimental results was done for the example of particle size enlargement at different flow rate of the binding solution feed. A good correlation between theoretical and experimental data was found for both the mean particle size growth and the fraction size distribution at different moments of time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computational and Experimental Study of Granulation in Fluidized Bed Reactor

Mizonov

Mitrofanov

Tannous

et al. 2019

IVKKT

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A study of stability of difference scheme of Markov counting chain method for fluidization modeling

et al. 2021

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Devices with a fluidized bed of granular material are applied in many energy power technology processes. The fluidized bed is a heterogeneous system, so mathematical models assuming its spatial discretization are necessary for its proper description. Markov chain theory is one of the most effective tools for the mathematical description of the fluidized bed structure. Many research papers are devoted to the issues of the theory application when developing mathematical models of various technological processes in the fluidized bed. At the same time, much less attention is paid to the issue of stability analysis of the proposed algorithms. Thus, it is a highly topical issue to analyze the computational stability of models of fluidized bed based on the mathematical principles of the Markov chain theory. The Markov chain approach is used as a mathematical basis for modeling of the flow patterns in a fluidized bed. The parametric identification of the model is performed using the dependencies known from the scientific papers, and the transition matrices are aligned with the physical parameters of the mass flows, which makes the proposed model nonlinear. The mixed criterion of the stability algorithm is formulated. It shows the influence of the spatiotemporal parameters of the problem sampling on the stability of computational procedures. The stability of the difference scheme to calculate formation of a fluidized bed of a monodisperse granular material is studied. The influence of the time sampling frequency on the stability of the resulting solution is considered. The effect of various parameters of the model on the loss of computational stability is estimated. It is proved that the time and spatial sampling frequencies should be chosen as a result of a mixed stability criterion. The study proves that the methodology of the Markov chain theory is an acceptable tool to describe the structure of such particle systems as a fluidized bed. It is established that macro-diffusion parameter of particle motion is the most influential in the process of computational stability loss. Thus, on the one hand, it is relevant to conduct further comparative studies of existing models of macrodiffusion, and on the other hand, it is possible to use models based on the theory of Markov chains considering the proposed stability criterion.

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Theoretical Study of Granulation Kinetics in a Batch Fluidized Bed

Cited by 2 publications

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Computational and Experimental Study of Granulation in Fluidized Bed Reactor

Computational and Experimental Study of Granulation in Fluidized Bed Reactor

A study of stability of difference scheme of Markov counting chain method for fluidization modeling

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