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Predicting granular growth process: model development, implementation and assessment for industrial applications

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TitleInfo
Title
Predicting granular growth process: model development, implementation and assessment for industrial applications
Name (type = personal)
NamePart (type = family)
Tamrakar
NamePart (type = given)
Ashutosh
NamePart (type = date)
1988-
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Ashutosh Tamrakar
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Ramachandran
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Rohit
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Rohit Ramachandran
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Advisory Committee
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chair
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Ierapetritou
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Marianthi
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Marianthi Ierapetritou
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Advisory Committee
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internal member
Name (type = personal)
NamePart (type = family)
Glasser
NamePart (type = given)
Benjamin
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Benjamin Glasser
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Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Shapley
NamePart (type = given)
Nina
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Nina Shapley
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Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Piccione
NamePart (type = given)
Patrick M
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Patrick M Piccione
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
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NamePart
School of Graduate Studies
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school
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Text
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theses
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2019
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2019-05
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2019
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract (type = abstract)
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.
Subject (authority = local)
Topic
Granular modeling
Subject (authority = RUETD)
Topic
Chemical and Biochemical Engineering
Subject (authority = LCSH)
Topic
Particles -- Computer simulation
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
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ETD_9835
PhysicalDescription
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application/pdf
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text/xml
Extent
1 online resource (xxiv, 238 pages) : illustrations
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-1vkw-hm42
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Tamrakar
GivenName
Ashutosh
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-04-12 11:34:31
AssociatedEntity
Name
Ashutosh Tamrakar
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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