High performance computing for modelling of stereolithography process

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Kumar, Sandeep: High Performance Computing for Modelling of Stereolithography Process. Hannover : Institut für Kontinuumsmechanik, Leibniz Universität Hannover, 2022 (Leibniz Universität Hannover, Institut für Kontinuumsmechanik ; B 22/1), viii, 98 S. ISBN 978-3-941302-46-4

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Sum total of downloads: 360

In this dissertation, a state-of-the-art 3D computational model has been developed for Stereolithography process to investigate the evolution of properties in a multi-physics framework using Stabilized Optimal Transportation Meshfree (OTM) method based on a continuum approach. In order to accelerate the computational performance, HPC framework of the OTM method has been developed. Stereolithography process is a complex process in the sense that several physical processes are involved therein. In this work, some of the key phenomena incorporated in the modeling framework are highly coupled thermo-chemo-mechanical evolution of resin properties and propagation of the UV laser through the resin. The photopolymerization is driven by the interaction of fluid resin with the UV light and consequently generates heat due to its exothermic nature and resulting in building up of mechanical stresses. The numerical and geometrical complexities arising from these phenomena pose serious challenges and complications in grid-based techniques such as Finite element (FE). Generally, such issues are referred to as mesh distortion. OTM based computational modeling is one solution to these issues. The method is quite new in the field of Stereolithography simulation and it is efficient in capturing the deformations generated during printing process. Moreover, parallelization using MPI with an objective for scalability on large scale CPU clusters reduces the computational efforts. And, the obtained results leads to highly scalable results. The developed tool can be employed to optimize the material and process parameters during the printing process to achieve improved accuracy in the printed parts.
License of this version: CC BY 3.0 DE
Document Type: DoctoralThesis
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 264 73.33%
2 image of flag of United States United States 25 6.94%
3 image of flag of India India 11 3.06%
4 image of flag of China China 11 3.06%
5 image of flag of Singapore Singapore 5 1.39%
6 image of flag of Hong Kong Hong Kong 5 1.39%
7 image of flag of Luxembourg Luxembourg 4 1.11%
8 image of flag of France France 4 1.11%
9 image of flag of Austria Austria 4 1.11%
10 image of flag of Turkey Turkey 3 0.83%
    other countries 24 6.67%

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