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• W4317584388 abstract "In this study, a genetic algorithm is used to find carbon nanotube bundle microstructures whose bulk elastic-orthotropic properties optimally match desired bulk mechanical properties. Previous molecular dynamics simulations provide material properties for the carbon nanotube bundles. Three-dimensional finite-element micromechanics analyses of multi-bundle microstructures are performed with periodic boundary conditions to yield bulk elastic-orthotropic properties. Many configurations of carbon nanotube bundle microstructures are provided to a convolutional neural network for training. The convolutional neural network is incorporated into a genetic algorithm that searches the bundle microstructure design space for configurations that optimally achieve target bulk properties. The optimized configurations are re-analyzed via finite element simulations to assess the approach." @default.
• W4317584388 created "2023-01-21" @default.
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• W4317584388 date "2023-01-19" @default.
• W4317584388 modified "2023-09-27" @default.
• W4317584388 title "CNN-Informed Genetic Algorithm for Optimizing Mechanical Performance of Carbon Nanotube Microscale Bundles" @default.
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• W4317584388 doi "https://doi.org/10.2514/6.2023-0771" @default.
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