A semi-theoretical model for simulating the temporal evolution of moisture-temperature during industrial fluidized bed granulation
| Autor: | Xiaorong He, Leon Schultz, Daniela Schröder, Martin Maus, Schwabe Robert J, Ecevit Bilgili, Pavol Rajniak, Yin Chao Tseng, Hossein Amini, Gulsad Kucuk |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Process modeling
Moisture Estimation theory Chemistry Pharmaceutical Evaporation Temperature Pharmaceutical Science 02 engineering and technology General Medicine Mechanics Models Theoretical 021001 nanoscience & nanotechnology 030226 pharmacology & pharmacy Excipients 03 medical and health sciences 0302 clinical medicine Scientific method Calibration Range (statistics) Environmental science Technology Pharmaceutical Process simulation 0210 nano-technology Physics::Atmospheric and Oceanic Physics Biotechnology |
| Zdroj: | European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V. 151 |
| ISSN: | 1873-3441 |
| Popis: | Moisture plays a major role in determining the attributes of granules prepared by fluidized bed granulation (FBG). Here, a semi-theoretical droplet-based evaporation rate model was developed and incorporated into moisture mass-enthalpy balances to simulate the temporal evolution of bed moisture-temperature. Experimental data from a GPCG30 unit were used to fit the model parameters. With only two fitting parameters, the model demonstrated excellent capability to describe the moisture-temperature evolution for a wide range of operating conditions. Then, in a global process model (GPM) approach, the evaporation parameters were fitted to multi-linear functions of inlet air temperature, binder concentration, and spray rate. The GPM was validated successfully by simulating a different data set which was not used in its calibration. As the GPM demonstrated a good predictive capability, it was further used to investigate the impacts of process parameters. Numerical simulations suggest that the proposed GPM predicts the experimentally well-established trends of moisture-temperature profiles in previously published data, proving the applicability of the GPM approach. This study has demonstrated the capabilities of simple process models as a practical approach to predict time-wise evolution of bed moisture-temperature profiles in industrial FBG modeling, while also pointing out their limitations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect