Text

theses

Growth of granular particles - whether desired or undesired - are quite common in various industrial operations from agro-chemical manufacturing to pharmaceutical product development to food and fine/specialty chemicals production. As such, their related problems and methods to predict their behavior have been widely discussed in various engineering fields. This work provides an in-depth description of the development, implementation and assessment of various predictive tools and techniques of granular growth processes including use of dimensionless groups, advanced computational models as well as multi-scale frameworks to improve the performance of these models. This study presents a comprehensive look at the current state-of-the-art computational techniques used in granular and multi-phase flows and presents a practical framework for incorporating design-based principles and developing predictive model-based analysis to understand granular processes through case studies. In the following thesis, three case studies involving manufacturing issues encountered in common unit operations are highlighted: (i) generation of undesired agglomeration during agitated filter-drying, (ii) formation of high/ low viscous regions during high-shear wet granulation with wet and dry binder addition, and (iii) prediction of granule size during top-spray fluidized bed wet granulation. The frameworks presented in this study demonstrate a pragmatic process model development methodology by efficiently coupling multi-scale/multi-phase simulations and numerical techniques which can be used for effective process design, development and scale-up purposes.

ETD_9835

Ph.D.

Includes bibliographical references

doi:10.7282/t3-1vkw-hm42

ETD doctoral

The author owns the copyright to this work.