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A level set approach for denoising and adaptively smoothing complex geometry stereolithography files

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Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means

Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means are prone to noise, surface irregularities and holes in an otherwise closed surface.

A general method for denoising and adaptively smoothing these dirty stereolithography files is proposed. Unlike existing means, this approach aims to smoothen the dirty surface representation by utilizing the well established levelset method. The level of smoothing and denoising can be set depending on a per-requirement basis by means of input parameters. Once the surface representation is smoothened as desired, it can be extracted as a standard levelset scalar isosurface.

The approach presented in this thesis is also coupled to a fully unstructured Cartesian mesh generation library with built-in localized adaptive mesh refinement (AMR) capabilities, thereby ensuring lower computational cost while also providing sufficient resolution. Future work will focus on implementing tetrahedral cuts to the base hexahedral mesh structure in order to extract a fully unstructured hexahedra-dominant mesh describing the STL geometry, which can be used for fluid flow simulations.

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Date Created
2014

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Investigating The Performance Of 3-D Printed Sorbents For Direct Air Capture Of CO2

Description

In this study, the stereolithography (SLA) 3D printing method is used to manufacture honeycomb-shaped flat sorbents that can capture CO2 from the air. The 3D-printed sorbents were synthesized using polyvinyl alcohol (PVA), propylene glycol, photopolymer resin, and an ion exchange

In this study, the stereolithography (SLA) 3D printing method is used to manufacture honeycomb-shaped flat sorbents that can capture CO2 from the air. The 3D-printed sorbents were synthesized using polyvinyl alcohol (PVA), propylene glycol, photopolymer resin, and an ion exchange resin (IER). The one-factor-at-a-time (OFAT) design-of-experiment approach was employed to determine the best combination ratio of materials to achieve high moisture swing and a good turnout of printed sorbents. The maximum load limit of the liquid photopolymer resin to enable printability of sorbents was found to be 44%. A series of moisture swing experiments was conducted to investigate the adsorption and desorption performance of the 3D-printed sorbents and compare them with the performance of IER samples prepared by a conventional approach. Results from these experiments conducted indicate that the printed sorbents showed less CO2 adsorptive characteristics compared to the conventional IER sample. It is proposed for future research that a liquid photopolymer resin made up of an IER be synthesized in order to improve the CO2-capturing ability of manufactured sorbents.

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Date Created
2020