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An Integrated Numerical Method to Predict the Strain Sensing Behavior of Flexible Conductive Fibers under Electric–Thermal Conditions.

Authors :
Wang, H.
Xue, P.
Zhu, W. L.
Source :
Journal of Materials Engineering & Performance; Jun2019, Vol. 28 Issue 6, p3309-3319, 11p
Publication Year :
2019

Abstract

Flexible conductive textiles have attracted an increasing amount of attention due to being flexible and stretchable with multi-functions, in addition to the strain sensing function. In this paper, an integrated numerical method is established to predict the strain sensing behavior of PPy-coated flexible conductive fibers. Based on our previous investigation on the strain sensing behavior of the PPy-coated elastic conductive fibers, it has been known that the main strain sensing mechanisms of the conductive fibers are micro-cracks opening under stretching and closing under unloading. Therefore, in the numerical approach, extended finite element method is used to simulate the multi-crack initiation and propagation. Then, by establishing a representative element model including a single crack, the resistance variation with the increase in crack width/depth can be obtained using the electric–thermal package in ABAQUS software. Combining the relationship between crack width and strain, the relationship between fractional increment in resistance ( Δ R / R 0 ) and the strain can be obtained. The prediction of the fractional increment in resistance ( Δ R / R 0 ) versus strain is consistent with the experimental results of PPy-coated Lycra fibers. The new integrated method is further verified by experimental results of PPy-coated XLA fibers, showing that the integrated numerical approach can capture the complicated strain sensing mechanisms of PPy-coated elastic fibers and predict the strain sensing behavior of flexible conductive fibers. This approach will make it possible to shorten the period, and reduce the cost in R&D of the PPy-coated electrically conductive fibers, comparing with the corresponding experimental work. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10599495
Volume :
28
Issue :
6
Database :
Complementary Index
Journal :
Journal of Materials Engineering & Performance
Publication Type :
Academic Journal
Accession number :
137665334
Full Text :
https://doi.org/10.1007/s11665-019-04091-2