Electromechanical self-sensing characteristics of carbon fiber composites: Multi-level mechanisms and equivalent electrical circuit model based analysis
- Authors
- Roh, Hyung Doh
- Issue Date
- Jun-2025
- Publisher
- Elsevier Ltd
- Keywords
- Carbon fiber; Composite; Smart material; Structural health monitoring
- Citation
- Engineering Structures, v.333, pp 1 - 15
- Pages
- 15
- Indexed
- SCIE
SCOPUS
- Journal Title
- Engineering Structures
- Volume
- 333
- Start Page
- 1
- End Page
- 15
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/123659
- DOI
- 10.1016/j.engstruct.2025.120102
- ISSN
- 0141-0296
1873-7323
- Abstract
- The electromechanical self-sensing ability of the carbon fiber composites was investigated by analyzing the change in the electrical resistance when subjected to mechanical deformation or failure. This behavior is due to the combined effects of the intrinsic piezoresistivity of the carbon fibers and intra-tow/inter-tow/inter-ply interactions, which are pertinent to the bundled (tow-level), woven/unidirectional (ply level), and stacked (laminate-level) nature of the laminated composites. The mechanisms were interpreted using electrically equivalent circuit models, which aided in numerical analysis and sensitivity prediction by considering the electrical resistance changes with respect to tensile deformation. The proposed model included the electromechanical behavior of multiscale carbon fibers, such that the gauge factors are 0.19 for the monofilament and 0.217 for the tailored composite. In addition, the terms with respect to the bending direction were considered because the composite exhibited various resistance changes in terms of the fiber and loading directions. By understanding the electromechanical mechanisms using the proposed models, the self-sensing ability and sensitivity of carbon fiber composites can be tailored. A proof-of-concept of Carbon-fiber-reinforced plastics (CFRP) self-sensing was demonstrated on a 3D-printed bridge structure, in which The CFRP underneath the bridge enabled real-time deflection monitoring. © 2025 Elsevier Ltd
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Collections - COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF MECHANICAL ENGINEERING > 1. Journal Articles

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