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  4. Topology optimization with nozzle size restrictions for material extrusion-type additive manufacturing

Topology optimization with nozzle size restrictions for material extrusion-type additive manufacturing

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Author(s)
Carstensen, Josephine V
Date Issued
June 2020
Journal
Structural and Multidisciplinary Optimization
Publisher
Springer Science and Business Media LLC
Citation
Carstensen, Josephine V. "Topology optimization with nozzle size restrictions for material extrusion-type additive manufacturing." Structural and Multidisciplinary Optimization 62, 5 (June 2020): 2481–2497 © 2020 Springer-Verlag GmbH Germany, part of Springer Nature
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Author's final manuscript
Abstract
Topology optimization that is tailored to additive manufacturing constraints and possibilities is an important area of research with direct implications on solution manufacturability. This paper focuses on implementing the nozzle size constraint that is associated with most material extrusion-type additive manufacturing processes, such as fused filament fabrication and concrete 3D printing. The constraint is especially important for manufacturability in situations where the size of used nozzle is large in comparison with the size of the design domain. This paper suggests a new projection-based algorithm that embeds material extrusion-type primitives into the projection methodology used for material distribution approaches to topology optimization. Projection-based algorithms for continuum topology optimization have received considerable attention in recent years due to their ability to improve manufacturability in a flexible and computationally efficient manner. A formulation for single-directional primitives is presented and extended to allow the use of two-directional primitives that can simulate a more realistic nozzle movement. The proposed algorithms are demonstrated on 2D benchmark problems and are shown to satisfy the imposed nozzle size restrictions.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/129539
DOI of Published Version
https://doi.org/10.1007/s00158-020-02620-5
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