Inverse design of truss lattice materials with superior buckling resistance

نویسندگان

چکیده

Abstract Manipulating the architecture of materials to achieve optimal combinations properties (inverse design) has always been dream scientists and engineers. Lattices represent an efficient way obtain lightweight yet strong materials, providing a high degree tailorability. Despite massive research done on lattice architectures, inverse design problem complex phenomena (such as structural instability) remained elusive. Via deep neural network genetic algorithm, we provide machine-learning-based approach inverse-design non-uniformly assembled lattices. Combining basic building blocks, our allows us independently control geometry topology periodic aperiodic structures. As example, architectures with superior buckling performance, outperforming traditional reinforced grid-like bio-inspired lattices by ~30–90% 10–30%, respectively. Our results insights into behavior beam-based lattices, opening avenue for possible applications in modern structures infrastructures.

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ژورنال

عنوان ژورنال: npj computational materials

سال: 2022

ISSN: ['2057-3960']

DOI: https://doi.org/10.1038/s41524-022-00938-w