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- W2912146683 abstract "Void detection in fiber-reinforced composites traditionally relies on precise density measurements before and after the physical removal of the polymer matrix; consequently, this method only provides data on the total volume of voids within the material without information about void sizes, shapes, and distributions. Despite advances in X-ray computed tomography, it is still challenging to quantitatively and convincingly characterize void content due to the complex X-ray physics of divergent, broad-spectrum laboratory X-ray sources. Here, we demonstrate that by using aligned high-energy and low-energy X-rays, dual-energy X-ray computed tomography provides high-quality images and phase-based segmentation that allows for clear distinction between air, polymer matrix, and reinforcing fibers. We verify the method on several fiber-reinforced composite samples: epoxy-glass fiber composites fabricated by vacuum-assisted resin transfer molding and by light resin transfer molding (light resin transfer molding), and a carbon fiber composite fabricated via vacuum-assisted resin transfer molding." @default.
- W2912146683 created "2019-02-21" @default.
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- W2912146683 date "2019-01-31" @default.
- W2912146683 modified "2023-10-10" @default.
- W2912146683 title "Dual-energy X-ray computed tomography for void detection in fiber-reinforced composites" @default.
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- W2912146683 doi "https://doi.org/10.1177/0021998319827091" @default.
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