Effect of geometric design parameters on contractile SMA knitted actuator performance

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Abstract

Shape memory alloy (SMA) knitted actuators are a type of functional fabric that uses shape memory alloy wire as an active fiber within a knitted textile. Through intentional design of the SMA knitted actuator geometry, various two- and threedimensional actuation motions, such as scrolling and contraction [1], can be accomplished. Contractile SMA knitted actuators leverage the unique thermo-mechanical properties of SMA wires by integrating them within the hierarchical knitted structure to achieve large distributed uniaxial contractions and variable stiffness behavior upon thermal actuation. During the knit manufacturing process, the SMA wire is bent into a network of interlacing adjacent loops, storing potential energy within the contractile SMA knitted actuator. Thermal actuation above the wire-specific austenite finish temperature leads to a partial recovery of the bending deformations, resulting in large distributed uniaxial contraction (15-40 % actuation contraction observed) of the SMA knitted actuator. The achievable load capacity and %-actuation contraction are dependent on the geometric loop parameters of the contractile SMA knitted actuator. While exact descriptions of the geometric loop parameters exist, a reduction of the geometric complexity is advantageous for high-level contractile SMA knitted actuator design procedures. This paper defines a simple geometric measure, the non-dimensional knit density, and experimentally correlates the contractile SMA knitted actuator performance to this measure. The experimentally demonstrated dependency of relevant actuator metrics on the knit density and the wire diameter, suggests the usability of the simplified geometry definition for a high-level contractile SMA knitted actuator design.

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APA

Eschen, K., & Abel, J. (2017). Effect of geometric design parameters on contractile SMA knitted actuator performance. In ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017 (Vol. 2). American Society of Mechanical Engineers. https://doi.org/10.1115/SMASIS2017-3926

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