Polydisperse fluidization—I. Basic equations

Buyevich, Yu.A.; Kapbasov, Sh. K.

doi:10.1016/0009-2509(94)85094-1

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…[9] developed a correlation for the mixing index for a size-variant and equal-density system of particles as: beds with mono-density particles with relatively narrow size distribution. Buyevich and Kapbasov [12] studied the momentum equations governing vertical distribution of particles of different sizes and densities in a homogeneous fluidized bed and concluded that the conventional kinetic theory of gaseous mixtures, in which such force differences are usually not taken into account and the relative motion is conceived as a phenomenon of purely diffusional origin, is sufficient for expressing mean forces of interaction between the particulate components in terms of observable variables.…”

Section: Introductionmentioning

confidence: 99%

Effect of promoters and secondary fluidizing medium on mixing: statistical and ANN approaches

Mohanty¹,

Mohanty²,

Roy

et al. 2008

Asia-Pacific J Chem Eng

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Factorial design (statistical approach) and artificial neural network (ANN) models have been developed for the prediction of mixing the index with four system parameters, such as static bed heights, average particle densities, average particle sizes and gas velocities, under four different experimental conditions, viz., only primary air, simultaneous primary and secondary air, disc promoter and rod promoter. The values of the mixing index obtained through the developed models are found to agree well with their experimental counterparts. It has also been found from these investigations that under simultaneous primary and secondary air supply conditions the best mixing performance is achieved, i.e. I M ≈ 1.0, as compared to rod promoter, disc promoter, and only primary air supply. 

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Section: Introductionmentioning

confidence: 99%