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Topology Optimization of Composite Self-Deployable Thin Shells with Cutouts

Ferraro, S. and Pellegrino, S. (2019) Topology Optimization of Composite Self-Deployable Thin Shells with Cutouts. In: AIAA Scitech 2019 Forum. American Institute of Aeronautics and Astronautics , Reston, VA, Art. No. 2019-1524. ISBN 978-1-62410-578-4.

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The paper presents topology optimization studies of selfs-deployable joints in thin-walled tubular structures. The joints are made entirely of ultra-thin, fiber reinforced composite materials. The objective of this research is to strategically position cutouts on the joints so that they can fold without failing, while maximizing the deployed bending stiffness. The optimal shape and position of cutouts are the results of concurrent topology optimization of these composite, thin-shell joints with geometrical non-linearities, due to their folding and self-deployable nature. Numerical methods to accurately detect failure are implemented and results from a novel level-set method for topology optimization are compared to results from classical parametric optimization and preliminary designs based on physical intuition.

Item Type:Book Section
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URLURL TypeDescription ItemJournal Article
Ferraro, S.0000-0002-6038-7863
Pellegrino, S.0000-0001-9373-3278
Additional Information:© 2019 by the American Institute of Aeronautics and Astronautics, Inc. Published Online: 6 Jan 2019. This work was supported by a NASA Space Technology Research Fellowship. S.F. would like to acknowledge the mentorship of Dr. William Doggett, NASA Langley, and Thibaud Talon, Caltech, for exchange of ideas.
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NASA Space Technology Research FellowshipUNSPECIFIED
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AIAA Paper2019-1524
Record Number:CaltechAUTHORS:20210913-222227787
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Official Citation:Serena Ferraro and Sergio Pellegrino. "Topology Optimization of Composite Self-Deployable Thin Shells with Cutouts," AIAA 2019-1524. AIAA Scitech 2019 Forum. January 2019; DOI: 10.2514/6.2019-1524
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110824
Deposited By: Tony Diaz
Deposited On:13 Sep 2021 22:39
Last Modified:13 Sep 2021 22:39

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