The overarching goal of this study is to quantitatively understand the interactions between material properties, process parameters, equipment design and environmental conditions to predict product performance of granules as product performance is critical to the value of granulated products. In this study, multi-scale predictive models are presented for granulation processes combining key material properties and process parameters with transport phenomena. Results obtained from the study enables a more quantitative and predictive understanding of granulation. Furthermore, the improved multi-scale model formulations can be used to alleviate labor- and capital-intensive experimentation that currently plagues industrial processes.
|Original language||English (US)|
|Number of pages||5|
|Journal||Computer Aided Chemical Engineering|
|State||Published - Jun 20 2011|
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Computer Science Applications