The Relative Activation Energy of Food Materials: Important Parameters to Describe Drying Kinetics

Computational Modeling of Drying of Pharmaceutical Wet Granules in a Fluidized Bed Dryer Using Coupled CFD-DEM Approach

Drying of wet granules in a fluidized bed dryer is an important part of the pharmaceutical tablet manufacturing process. Complicated gas-solid flow patterns appear in the fluidized bed dryer, and interphase momentum, heat, and mass transfer happen during the drying process. A coupled computational fluid dynamics (CFD)-discrete element method (DEM)-based approach was used to model the drying process of pharmaceutical wet granules in a fluidized bed dryer. The evaporation of water from the surfaces of the particles and the cohesion force between the particles due to the formation of liquid bridges between the particles were also considered in this model. The model was validated by comparing the model predictions with the experimental data available from the literatures. The validated model was used to investigate the drying kinetics of the wet granules in the fluidized bed dryer. The results from numerical simulations showed that the dynamics and rate of increase of temperature of wet particles were considerably different from those of dry particles. Finally, the model was used to investigate the effects of inlet air velocity and inlet air temperature on the drying process. The model predicted increase in drying rate with the increase of inlet air velocity and inlet air temperature. This model can help not only to understand the multiphase multicomponent flow in fluidized bed dryer but also to optimize the drying process in the fluidized bed dryer.

Nonlinear Model-Based Inferential Control of Moisture Content of Spray Dried Coconut Milk

The moisture content of a powder is a parameter crucial to be controlled in order to produce stable products with a long shelf life. Inferential control is the best solution to control the moisture content due to difficulty in measuring this variable online. In this study, fundamental and empirical approaches were used in designing the nonlinear model-based inferential control of moisture content of coconut milk powder that was produced from co-current spray dryer. A one-dimensional model with integration of reaction engineering approach (REA) model was used to represent the dynamic of the spray drying process. The empirical approach, i.e., nonlinear autoregressive with exogenous input (NARX) and neural network, was used to allow fast and accurate prediction of output response in inferential control. Minimal offset (<0.0003 kg/kg) of the responses at various set points indicate high accuracy of the neural network estimator. The nonlinear model-based inferential control was able to provide stable control response at wider process operating conditions and acceptable disturbance rejection. Nevertheless, the performance of the controller depends on the tuning rules used.

Drying colloidal systems: Laboratory models for a wide range of applications

The drying of complex fluids provides a powerful insight into phenomena that take place on time and length scales not normally accessible. An important feature of complex fluids, colloidal dispersions and polymer solutions is their high sensitivity to weak external actions. Thus, the drying of complex fluids involves a large number of physical and chemical processes. The scope of this review is the capacity to tune such systems to reproduce and explore specific properties in a physics laboratory. A wide variety of systems are presented, ranging from functional coatings, food science, cosmetology, medical diagnostics and forensics to geophysics and art.