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Using statistical methods to optimize powder flow measurements and to predict powder processing performance

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TitleInfo
Title
Using statistical methods to optimize powder flow measurements and to predict powder processing performance
Name (type = personal)
NamePart (type = family)
Koynov
NamePart (type = given)
Sara
NamePart (type = date)
1985-
DisplayForm
Sara Koynov
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Glasser
NamePart (type = given)
Benjamin
DisplayForm
Benjamin Glasser
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Muzzio
NamePart (type = given)
Fernando
DisplayForm
Fernando Muzzio
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Callegari
NamePart (type = given)
Gerardo
DisplayForm
Gerardo Callegari
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Borghard
NamePart (type = given)
Bill
DisplayForm
Bill Borghard
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2015
DateOther (qualifier = exact); (type = degree)
2015-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2015
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The flow behavior of powders - key raw materials, intermediates, and final products across many industries - is poorly understood, making the prediction of manufacturability and process performance difficult. Common manufacturing problems include non-uniform flow, jamming, segregation, and content uniformity issues. Due to the complex nature of granular materials, their flow behavior, typically, cannot be described using a single parameter. Many methods have been developed that utilize a range of sample sizes and characterize the material in a variety of consolidation states. The path for using these techniques for increasing process understanding remains unclear since the relationships between material properties and powder processing conditions remain partly unknown. In this work, principal component analysis of large material property datasets was used to identify the most relevant material properties for a given application. This statistical approach was demonstrated using a database of raw material properties. The number of material properties needed to explain the observed variability was reduced to the minimum, while retaining the same predictive capability as the original dataset. Additionally, the three characterization techniques that provided the most predictive capability were identified. Fundamental understanding of the characterization techniques is critical for the successful application of material flow properties to solids processing operations. Two commonly used techniques are the shear cell and compressibility tests. These tests were also among those previously identified as relevant for distinguishing maximally between raw materials. It was found that different shear cells yield statistically different measurements even when testing the same powders under the same consolidation stress. Further, a novel compressibility method for reducing the amount of material required, to less than 50mg, for measuring flow properties was developed. The use of material property characterization to increase process understanding was demonstrated through a case study of axial mixing in a rotating drum. The axial dispersion coefficient was found to be dependent on the material properties and increased with decreasing flowability. In this case, particle size, shear cell, and compressibility measurements explained 95% of the variation observed in the axial dispersion coefficient.
Subject (authority = RUETD)
Topic
Chemical and Biochemical Engineering
Subject (authority = ETD-LCSH)
Topic
Powders
Subject (authority = ETD-LCSH)
Topic
Bulk solids flow
Subject (authority = ETD-LCSH)
Topic
Statistics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6285
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xi, 158 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Sara Koynov
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T32F7Q9K
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
Koynov
GivenName
Sara
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-04-09 12:30:58
AssociatedEntity
Name
Sara Koynov
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
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.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2015-11-30
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after November 30th, 2015.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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