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- W4285036623 abstract "In prosthesis, functionally graded biocomposites are the potential materials that can fullfil the feasible requirements due to their enhanced characteristics. In this study, deformation characteristics of heterogeneous functionally graded biocomposite sinusoid structures are examined under various parametric conditions. Here the biocomposite structure is comprised of titanium at the lower surface and hydroxyapatite at the upper surface and graded in-between along the thickness. Two distinguished micromechanical material models, i.e., Voigt’s rule-of-mixture and Mori-Tanaka homogenization schemes, in conjunction with the power-law function, are employed to compute the through-the-thickness heterogeneous material properties. The kinematic equations are developed using third-order shear-deformation theory in conjunction with general differential curvature equation, which is used to define the sinusoid geometry. The final equilibrium equations are solved using isoparametric finite element approximations via minimum total potential energy principle. To exhibit the accuracy of the present finite element model, a validation test is executed by comparing present results with the published results. Numerical experimentations are demonstrated to confirm the robustness of present model for different set of conditions. The comprehensive parametric study reflects that the impacts of various parameters, such as power-law index, aspect ratio, side-to-thickness ratios, amplitude ratio, and loading and support conditions, on the deflection responses of functionally graded biocomposite sinusoid structure are significant." @default.
- W4285036623 created "2022-07-12" @default.
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- W4285036623 date "2022-07-11" @default.
- W4285036623 modified "2023-09-24" @default.
- W4285036623 title "Micromechanics-Based Finite Element Analysis of HAp-Ti Biocomposite Sinusoid Structure Using Homogenization Schemes" @default.
- W4285036623 doi "https://doi.org/10.1201/9781003158813-8" @default.
- W4285036623 hasPublicationYear "2022" @default.
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