(203b) Infrared Temperature Experiments and DEM Simulations of Heat Transfer in an Agitated Dryer | AIChE

(203b) Infrared Temperature Experiments and DEM Simulations of Heat Transfer in an Agitated Dryer


Hartmanshenn, C. - Presenter, Rutgers University
Glasser, B. - Presenter, Rutgers University
Khinast, J. G., Graz University of Technology
Halota, M., Rutgers University
Patel, S. D., Rutgers University
Chakraborty, N., Rutgers University
Papageorgiou, C. D., Takeda Pharmaceuticals International Co.
Mitchell, C., Takeda Pharmaceuticals International Co.
Quon, J., Takeda Pharmaceuticals
Drying is typically one of the last steps of the manufacturing process for an active pharmaceutical ingredient (API). After crystallization and filtration, the wet bed of API needs to be dried into a powder with a desired moisture content before it can be mixed with other excipients and formulated into a drug product. A common method used by the pharmaceutical industry to carry out API drying is agitated drying, where the API is heated inside a cylindrical vessel while being mixed by an impeller to help improve temperature and moisture uniformity in the particle bed. Agitated drying can be one of the most complicated and delicate phases of the process, and it sometimes remains poorly understood and difficult to optimize. Simultaneous and transient changes in heat transfer, mass transfer, flow, and physicochemical properties of the material during drying make it challenging to thoroughly understand the system. Enhancing fundamental knowledge about the process could be key to enabling the design of efficient and robust operating protocols.

In this work, we isolate the heat transfer element of drying and focus on studying it on its own. The idea is that if we can decouple the different facets of drying and understand them on their own first, we can eventually study their combined interactions more easily. We conduct heat transfer experiments using a laboratory scale agitated dryer and an infrared camera to measure the temperature of the surface of a particle bed over time. The temperature data collected by the thermal camera is used to compute the heat transfer coefficient for the system as well as the temperature standard deviation, giving information about both the mean temperature of the bed and its temperature uniformity. Using this methodology, we investigate how operating conditions, such as the impeller rotation rate, influence heat transfer. The experiments are carried out using glass beads as well as more pharmaceutically relevant materials such as citric acid. Next, we present a comparison between the experimental results and discrete element method (DEM) simulations. The model makes use of a particle-particle and particle-wall conductive heat transfer model to describe the system. Overall, despite the simplicity of the heat transfer model, we find a fairly good agreement between the simulations and the experiments. This suggests that the model can serve as a good starting point towards better understanding how the rate of heat transfer and the temperature uniformity of a particle bed can be optimized in an agitated dryer.