Effect of secondary fluidizing medium on hydrodynamics of gas–solid fluidized bed—Statistical and ANN approaches

Investigations have been carried out in a cylindrical gas–solid fluidized bed to study the effect of secondary fluidizing medium on bed pressure drop, fluctuation and expansion ratios. Artificial neural network (ANN) and factorial design (statistical approach) models have been developed to predict pressure drop, fluctuation and expansion ratios with varying gas flow rates, bed heights, particle sizes and particle densities. The values of pressure drop, fluctuation and expansion ratios predicted by the developed models for primary, and simultaneous primary and secondary fluidizing media have been found to agree well with the corresponding experimental values. Owing to secondary air supply, the column is divided into two sections, viz., the upper and the lower. In order to improve the quality of fluidization and to increase its applicability, the fluidizer can be operated in higher velocity ranges, i.e., Gf ≥ 2Gmf, in the case of simultaneous primary and secondary air supply.