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- W4313593658 endingPage "108085" @default.
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- W4313593658 abstract "Triply periodic minimal surface (TPMS) is an effective filling architecture in porous ceramic artificial bone for its great bionic characteristics and self-supporting properties. However, design optimization of TPMS architecture remains a huge challenge due to the convoluted multi parameter-property relationship. In this study, optimization of TPMS structure for composite titania ceramic is accelerated by using the multi-objective optimization algorithm guided finite element method (FEM) simulation. According to the FEM analysis on thickness (Pt), array number (Pa) and constant number (Pc) as verified by compression testing and fluid experiment, Pt and Pa in TPMS structures are the key factors to force reaction, while Pa mainly determined the pressure drop. With Pc increasing, the pressure drops initially increased and decreasing after Pc=0. Bayesian optimization (BO) method is used to optimize both strength and permeability iteratively, in which the optimal Pareto frontier converges in less than 10 iterations. The parameter combination (Pt=0.28, Pc=-0.49, Pa=3.5) in best performing TPMS structure yields suitable modulus and permeability required for practical bone filling application, with 1.21 GPa in strength and 4.03 × 10−9 m−2 in permeability." @default.
- W4313593658 created "2023-01-06" @default.
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- W4313593658 date "2023-04-01" @default.
- W4313593658 modified "2023-10-17" @default.
- W4313593658 title "Multi-objective Bayesian optimization accelerated design of TPMS structures" @default.
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- W4313593658 doi "https://doi.org/10.1016/j.ijmecsci.2022.108085" @default.
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