Hydrodynamic behaviour of Cellets^(TM)(Ph.Eur./USP)in a spouted bed using image processing method

The hydrodynamic behaviour of the spouted bed in the pharmaceutical industries has been found to be less addressed.The present paper has focused on the hydrodynamic characteristics of a spouted bed where the Cellets^(TM)(Ph.Eur./USP)is adopted as the bed material.Experiments are carried out with three different static bed heights(H_(0))of shallow depth(2D_(i)≤H_(0)<3D_(i))using two different particle sizes.The spouted bed employed with D_(i)/D_(0) of 5 has given the experimental information on external spouting(Ues)by mapping the pressure drop,and fountain height(H_(f))against the superficial gas velocity(U_(g))is rep-resented with the image contours,which show the intrinsic behaviour.All the 1000 μm and 700 μm particles have been found to exhibit symmetric and asymmetric spouting.With increasing U_(g),the fully suspended particles are limited to a certain height in the freeboard region due to the gas-solid cross-flow,which implies the clusters have identified with the image processing method.

ANN modeling for diffusivity of mushroom and vegetables using a fluidized bed dryer

Drying characteristics in terms of diffusivity were studied for mushrooms and different vegetables in a fluidized bed dryer. Drying characteristics with falling rate regime were computed for all the sampi^z. Effective diffusivity of each sample was calculated. Mass transfer coefficients were determined. Mass transfer kinetics for drying of different samples was also found out. Correlations for the diffusivity of samples were developed by relating the experimentally observed data with the different system parame- ters on the basis of regression analysis. The developed correlations for effective moisture diffusivity of the samples are validated by artificial neural network （ANN） modeling. Finally calculated values of diffusivity obtained through both the methods are compared with the experimentally measured values which show a very good approximation thereby indicating the wide applicability of the developed correlations for industrial uses.

Segregation characteristics of irregular binaries in gas solid fluidized beds——An ANN-approach

Binary mixtures of irregular materials of different particle sizes and/or particle densities are fluidized in a 15-cm diameter column with a perforated plate distributor. An attempt has been made in this work to determine the segregation characteristics of jetsam particles for both the homogeneous and heterogeneous binary mixtures in terms of segregation distance by correlating it to the various system parameters, viz. initial static bed height, height of a layer of particles above the bottom grid, superficial gas velocity and average particle size and/or particle densities of the mixture through the dimensional analysis. Correlation on the basis of Artificial Neural Network approach has also been developed with the above system parameters thereby authenticating the development of correlation by the former approach. The calculated values of the segregation distance obtained for both the homogeneous and heterogeneous binary mixtures from both the types of ftuidized beds （i.e. under the static bed condition and the ftuidized bed condition） have also been compared with each other.