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Deposition Thickness Modeling and Parameter Identification for Spray Assisted Vacuum Filtration Process in Additive Manufacturing

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Date Issued:
2015
Abstract/Description:
To enhance mechanical and/or electrical properties of composite materials used in additive manufacturing, nanoparticles are often time deposited to form nanocomposite layers. To customize the mechanical and/or electrical properties, the thickness of such nanocomposite layers must be precisely controlled. A thickness model of filter cakes created through a spray assisted vacuum filtration is presented in this paper, to enable the development of advanced thickness controllers. The mass transfer dynamics in the spray atomization and vacuum filtration are studied for the mass of solid particles and mass of water in differential areas, and then the thickness of a filter cake is derived. A two-loop nonlinear constrained optimization approach is used to identify the unknown parameters in the model. Experiments involving depositing carbon nanofibers in a sheet of paper are used to measure the ability of the model to mimic the filtration process.
Title: Deposition Thickness Modeling and Parameter Identification for Spray Assisted Vacuum Filtration Process in Additive Manufacturing.
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Name(s): Mark, August, Author
Xu, Yunjun, Committee Chair
Gou, Jihua, Committee Member
Lin, Kuo-Chi, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2015
Publisher: University of Central Florida
Language(s): English
Abstract/Description: To enhance mechanical and/or electrical properties of composite materials used in additive manufacturing, nanoparticles are often time deposited to form nanocomposite layers. To customize the mechanical and/or electrical properties, the thickness of such nanocomposite layers must be precisely controlled. A thickness model of filter cakes created through a spray assisted vacuum filtration is presented in this paper, to enable the development of advanced thickness controllers. The mass transfer dynamics in the spray atomization and vacuum filtration are studied for the mass of solid particles and mass of water in differential areas, and then the thickness of a filter cake is derived. A two-loop nonlinear constrained optimization approach is used to identify the unknown parameters in the model. Experiments involving depositing carbon nanofibers in a sheet of paper are used to measure the ability of the model to mimic the filtration process.
Identifier: CFE0005974 (IID), ucf:50788 (fedora)
Note(s): 2015-12-01
M.S.A.E.
Engineering and Computer Science, Mechanical and Aerospace Engineering
Masters
This record was generated from author submitted information.
Subject(s): Spray atomization -- vacuum filtration -- additive manufacturing -- process modeling -- parameter identification
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0005974
Restrictions on Access: campus 2020-12-15
Host Institution: UCF

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