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Research Papers

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

[+] Author and Article Information
August Mark

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: augjmark@gmail.com

Yunjun Xu

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: Yunjun.Xu@ucf.edu

Jihua Gou

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: Jihua.Gou@ucf.edu

1Corresponding author.

Manuscript received March 7, 2016; final manuscript received September 16, 2016; published online October 18, 2016. Assoc. Editor: Zhijian J. Pei.

J. Manuf. Sci. Eng 139(4), 041002 (Oct 18, 2016) (7 pages) Paper No: MANU-16-1149; doi: 10.1115/1.4034890 History: Received March 07, 2016; Revised September 16, 2016

To enhance mechanical and/or electrical properties of composite materials used in additive manufacturing, nanoparticles are oftentimes deposited to form nanocomposite layers. To customize the mechanical and/or electrical properties of the final composite material, the thickness of such nanocomposite layers must be precisely controlled. A thickness model for filter cakes created through 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 to derive solid mass, water mass, and filter cake thickness differential area models. 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 filter paper are used to measure the ability of the model to mimic the filtration process.

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Figures

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Fig. 2

Spray visualization

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Fig. 1

Multilayer nanocomposite fabrication process

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Fig. 4

Thickness profile after 1 s of spray

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Fig. 5

Thickness profile after 4.2 s of spray

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Fig. 6

Thickness profile after 1 s of filtration

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Fig. 7

Thickness profile after 3 s of filtration

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Fig. 8

Thickness profile after 4.5 s of filtration

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Fig. 3

Experimental setup

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