Stochastical modeling of the granule size distribution in the agglomeration processes of powdered materials

Ceylan, Kadim; Kelbaliyev, G. I.

doi:10.1016/s0032-5910(00)00415-0

Cited by 10 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, instead of developing a Markov chain visualisation of this discrete process, the authors preferred to use a time-continuous representation to derive the steady-state and transient distributions of fi nes onto a carrier. Similarly, Ceylan and Kelbaliyev (2001) derived a time-continuous stochastic model using two Fokker-Planck equations to describe break-up of liquid and agglomeration of particles in a granulation drum. Again, it is sure that a Markov chain representation of these thoughts would have led to a more fl exible model without loss of generality.…”

Section: Size Enlargement and Particle Generationmentioning

confidence: 99%

Applications of Markov Chains in Particulate Process Engineering: A Review

Berthiaux

Mizonov

2004

Can J Chem Eng

View full text Add to dashboard Cite

Processes involving particles, are known to exhibit extremely unpredictable behaviour, mainly due to the mesoscopic nature of granular media. Understanding particulate processes, not only for intellectual satisfaction, but also for process design and operation, basically requires a systems approach in modelling. Because they combine simplicity and flexibility, the stochastic models based on the Markov chain theory are very valuable mathematical tools to this respect. However, they are still largely ignored by the whole core of chemical engineering researchers. This motivates the existence of this review paper, in which we examine the three traditional issues: mixing and transport, separation and transformation.

show abstract

Section: Size Enlargement and Particle Generationmentioning

confidence: 99%