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Multi-scale modeling of wet granulation processes
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Barrasso, Dana. Multi-scale modeling of wet granulation processes. Retrieved from https://doi.org/doi:10.7282/T37946NW

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TitleMulti-scale modeling of wet granulation processes
NameBarrasso, Dana (author); Ramachandran, Rohit (chair); Dutt, Meenakshi (internal member); Ierapetritou, Marianthi (internal member); Litster, James D. (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2015
Other Date2015-10 (degree)
SubjectChemical and Biochemical Engineering, Wetting, Granular materials
Extent1 online resource (xiii, 227 p. : ill.)
DescriptionWet granulation is a particle design process used to create larger granules from fine powder, improving flowability, compactibility, and homogeneity. Although it is widely used in the food, pharmaceutical, detergent, and fertilizer industries, it is often operated inefficiently, with high recycle ratios in continuous processes and high rejection rates in batch processes. In pharmaceutical applications, wet granulation is a critical step in tablet manufacturing that affects the uniformity and compactibility of the final dosage form. A model-based approach can be used to understand the effects of process parameters and material properties on critical quality attributes, developing a knowledge space for Quality by Design. Population balance modeling (PBM) provides a fundamental framework for tracking changes in particle properties over time, though it requires rate expressions and empirical parameters that cannot easily be measured. Discrete element modeling (DEM) is more mechanistic, tracking particles as they move through space and collide, but does not consider the complex mechanisms involved in wet granulation. Through this thesis, a multi-dimensional PBM for a continuous wet granulation process is presented. Model calibration and validation are performed using experimental data. A multi-scale PBM-DEM framework is developed and demonstrated using mechanistic rate expressions to enhance predictive capabilities. The multi-scale model is applied to realistic systems using computationally efficient techniques.
NotePh.D.
NoteIncludes bibliographical references
Noteby Dana Barrasso
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T37946NW
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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