Wang, Dong ; Li, Ling ; Serjouei, Ahmad ; Dong, Longteng ; Weeger, Oliver ; Gu, Guoying ; Ge, Qi (2021)
Controllable helical deformations on printed anisotropic composite soft actuators.
In: Applied Physics Letters, 2018, 112 (18)
doi: 10.26083/tuprints-00019840
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Controllable helical deformations on printed anisotropic composite soft actuators |
Language: | English |
Date: | 2021 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2018 |
Publisher: | AIP |
Journal or Publication Title: | Applied Physics Letters |
Volume of the journal: | 112 |
Issue Number: | 18 |
DOI: | 10.26083/tuprints-00019840 |
Corresponding Links: | |
Origin: | Secondary publication service |
Abstract: | Helical shapes are ubiquitous in both nature and engineering. However, the development of soft actuators and robots that mimic helical motions has been hindered primarily due to the lack of efficient modeling approaches that take into account the material anisotropy and the directional change of the external loading point. In this work, we present a theoretical framework for modeling controllable helical deformations of cable-driven, anisotropic, soft composite actuators. The framework is based on the minimum potential energy method, and its model predictions are validated by experiments, where the microarchitectures of the soft composite actuators can be precisely defined by 3D printing. We use the developed framework to investigate the effects of material and geometric parameters on helical deformations. The results show that material stiffness, volume fraction, layer thickness, and fiber orientation can be used to control the helical deformation of a soft actuator. In particular, we found that a critical fiber orientation angle exists at which the twist of the actuator changes the direction. Thus, this work can be of great importance for the design and fabrication of soft actuators with tailored deformation behavior. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-198409 |
Additional Information: | Supplement: https://aip.scitation.org/doi/suppl/10.1063/1.5025370/suppl_file/supplemental+materials_revised_unmarked.docx |
Classification DDC: | 500 Science and mathematics > 530 Physics 600 Technology, medicine, applied sciences > 600 Technology 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 16 Department of Mechanical Engineering > Cyber-Physical Simulation (CPS) |
Date Deposited: | 15 Dec 2021 10:24 |
Last Modified: | 15 Aug 2023 07:14 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/19840 |
PPN: | 510605419 |
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