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- W4387449346 abstract "Abstract Although composites are widely used and accepted across various industries, concerns still remain about the structural integrity of composite materials that are subject to fatigue and possible impact loading. The goal of this paper is to describe the design, development, manufacture, and characterization of a novel type of fiber-reinforced composite laminates with embedded nanocomposite-based strain sensors for potential real-time load monitoring and damage detection. The fiber reinforced composite laminates are composed of Kevlar fiber and an epoxy mixture, with a nanocomposite of carbon nanotubes (CNTs) and the same epoxy mixture. The CNT-based nanocomposite is 3D printed onto a strip of Kevlar fiber at a speed of 1 mm/s in a strain sensor pattern. Then, high-quality structural composites are manufactured by wet layup of 6 layers of Kevlar fiber, with the sensor embedded within. The manufactured composite laminates with embedded nanocomposite sensors are characterized under uniaxial-tension load to understand their in-situ sensing capability. To quantify the piezoresistive behavior, relative resistance change ΔR/R0 (where R0 is the initial resistance at the unloaded condition) is recorded while applying quasi-static tension at different strains in a cyclic manner. The mechanical properties and piezoresistive functionality of the composites will be determined as the samples undergo deformation. The corresponding piezoresistive change happening simultaneously can be used as a damage identification feature. This research can assist in the development of reliable and accurate damage detection technologies to improve the structural durability and operational safety of lightweight composite laminates for industry applications." @default.
- W4387449346 created "2023-10-10" @default.
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- W4387449346 date "2023-06-19" @default.
- W4387449346 modified "2023-10-11" @default.
- W4387449346 title "Lightweight Composites With 3D Printed Sensors for Real-Time Damage Detection" @default.
- W4387449346 doi "https://doi.org/10.1115/ssdm2023-107360" @default.
- W4387449346 hasPublicationYear "2023" @default.
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