(746d) Investigating Contact Drying in An Agitated Filter Dryer: Experiments and Simulations | AIChE

(746d) Investigating Contact Drying in An Agitated Filter Dryer: Experiments and Simulations


Sahni, E. - Presenter, University of Connecticut

Manufacturing is a critical component in procuring safe medications. However, it involves a series of unit operations each expected to modify material characteristics resulting in desired properties of the final product. Moreover, minimizing the production cost without compromising quality is another challenge. An improved understanding with the aid of first principle models would help in circumventing some of the process development concerns. Filter-dryer is principally installed because of subsequent overriding concerns: product sterility, toxicity, environmental emissions, and product quality.

Glassbeads and Lactose monohydrate were used as model compounds with ethanol as the solvent. The study investigates the effect of critical process parameters (wall temperature, impeller speed, pressure, and bed depth) in an agitated filter-dryer with temperature and solvent concentration profiles as the output attributes. A three dimensional numerical model was developed for demonstrating the contact heat transfer, by incorporating the algorithm for computing capillary and viscous forces exerted by the interstitial fluid between neighboring particles and heat transfer through liquid bridge and by contact conduction. Until recently, most of the DEM-based heat transfer work was either two-dimensional or in static granular beds. A three dimensional numerical model based on the extension of thermal particle dynamics was used to characterize the drying behavior of glassbead and lactose monohydrate in an agitated filter dryer.

The variation of the process parameters in the range investigated revealed that the rate of solvent drying is enhanced with increasing wall temperatures (40 – 80 °C) and decreasing bed depth (28 – 74 mm) due to increased driving force and reduced resistance to heat transfer respectively. The effect of agitation speed (5 – 25 rpm) was variable for both glassbeads and lactose monohydrate suggesting that the influence of operating parameter is dependent on the material properties of the compound under study. This change in the effect of speed was mainly attributed to frictional behavior which was demonstrated from flow dynamics using the velocity profiles. The velocity profiles of lactose showed the heap formation leading to formation of a recirculation zone due to high friction coefficients. Because of low friction and decreased roughness as in the case of glassbeads, recirculation zones were not created. This describes the ability of first principle models to provide comprehensive information and explanations relating the effect of material properties on operating parameter. Although mechanical agitation aids in improving heat transfer, consequences on particle size can be profound. Decrease in the particle size D[4,3] was evident with an increase in impeller speed and decrease in the bed depth due to increased collision frequency and reduction in the fill volume. It was concluded from the particle size distribution studies that attrition dominates the drying process when the loss of solvent drying rate was low and/or the shear rate was high. Under these conditions, the drying time was sufficiently long for particles to encounter countless particle-impeller and particle–particle collisions that can result in small fragments. Particle attrition was much higher towards the end of drying where solvent acting as a lubricant was reduced further. For higher dryer loads, the number of collisions decreased, stronger agglomerates were formed and thus agglomeration becomes more dominant. Thermograms obtained from conventional DSC scans demonstrate the melting of α-lactose monohydrate. This was further confirmed by PXRD. Regardless of small discrepancies, general trends obtained from simulations were similar suggesting that DEM not only offers a much more flexible approach with a direct relation between the material properties and the model parameters but also reduces the number of experiments and helps in better process understanding. Hence, process modeling based product development can reduce the time required to get products to market as well as the health care cost by saving resources.

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