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Multi-Objective Design Optimization of a Shape Memory Alloy Flexural Actuator

1
Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695-7910, USA
2
Flexiv Robotics Ltd., Santa Clara, CA 95054, USA
*
Author to whom correspondence should be addressed.
This paper is an extended version of a published conference paper: Haigh, C.D.; Crews, J.H.; Wang, S.; Buckner, G.D. Modeling and Experimental Validation of Shape Memory Alloy Bending Actuators. In Proceedings of the ASME Conference on Smart Materials, Adaptive Structures and Intelligent Systems, Stone Mountain, GA, USA, 19–21 September 2012.
Actuators 2019, 8(1), 13; https://doi.org/10.3390/act8010013
Received: 7 January 2019 / Revised: 31 January 2019 / Accepted: 10 February 2019 / Published: 16 February 2019
(This article belongs to the Special Issue Actuators Based on Shape Memory Alloys)
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Abstract

This paper presents a computational model and design optimization strategy for shape memory alloy (SMA) flexural actuators. These actuators consist of curved SMA wires embedded within elastic structures; one potential application is positioning microcatheters inside blood vessels during clinical treatments. Each SMA wire is shape-set to an initial curvature and inserted along the neutral axis of a straight elastic member (cast polydimethylsiloxane, PDMS). The elastic structure preloads the SMA, reducing the equilibrium curvature of the composite actuator. Temperature-induced phase transformations in the SMA are achieved via Joule heating, enabling strain recovery and increased bending (increased curvature) in the actuator. Actuator behavior is modeled using the homogenized energy framework, and the effects of two critical design parameters (initial SMA curvature and flexural rigidity of the elastic sleeve) on activation curvature are investigated. Finally, a multi-objective genetic algorithm is utilized to optimize actuator performance and generate a Pareto frontier, which is subsequently experimentally validated. View Full-Text
Keywords: shape memory alloy; microscale actuation; design optimization; genetic algorithm shape memory alloy; microscale actuation; design optimization; genetic algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Haigh, C.D.; Crews, J.H.; Wang, S.; Buckner, G.D. Multi-Objective Design Optimization of a Shape Memory Alloy Flexural Actuator. Actuators 2019, 8, 13.

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