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Evaluating the influence of porosity on the mechanical behavior of 3D-printed ceramic components using x-ray computed tomography and finite element modeling

International Journal of Mechanics of Solids · 2024 · Vol. 5(2) · pp. 18–22

Abstract

The influence of porosity on the mechanical behavior of 3D-printed ceramic components was evaluated using X-ray Computed Tomography (XCT) and Finite Element Modeling (FEM). High-purity alumina and zirconia ceramics were fabricated using stereolithography-based 3D printing and analyzed for their porosity characteristics, including size, distribution, and connectivity. XCT provided high-resolution, non-destructive visualization of internal structures, while FEM simulations were employed to predict stress distribution and failure mechanisms. Results showed a strong inverse correlation between porosity and mechanical properties, with zirconia exhibiting higher compressive strength (500 MPa), tensile strength (70 MPa), and fracture toughness (5.1 MPa·m⁰. ⁵) compared to alumina. Regression analysis revealed that a 1% increase in porosity led to significant reductions in strength and toughness. Discussion emphasized the critical role of porosity control in applications such as aerospace and biomedical engineering, where material performance is paramount. The study concludes that minimizing porosity through optimized manufacturing processes enhances the structural integrity of 3D-printed ceramics. The integration of XCT and FEM provides a robust framework for characterizing and improving ceramic components, paving the way for advanced material designs in additive manufacturing.

Additive Manufacturing and 3D Printing TechnologiesInjection Molding Process and PropertiesAdvanced Numerical Analysis TechniquesPorosityFinite element methodComputed tomographyMaterials scienceTomographyCeramicX-ray3d printedComposite materialBiomedical engineering
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Evaluating the influence of porosity on the mechanical behavior of 3D-printed ceramic components using x-ray computed tomography and finite element modeling · Scinovex