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A k‐means clustering machine learning‐based multiscale method for anelastic heterogeneous structures with internal variables

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Publication:6129648
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DOI10.1002/nme.6925MaRDI QIDQ6129648

Unnamed Author, Qi-Chang He, Julien Yvonnet, Benoît Bary

Publication date: 17 April 2024

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)


zbMATH Keywords

homogenizationnonlinearmultiscalemachine learning\(k\)-means clusteringFE2


Mathematics Subject Classification ID

Fracture and damage (74Rxx) Numerical and other methods in solid mechanics (74Sxx) Homogenization, determination of effective properties in solid mechanics (74Qxx)


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Accelerating the distance-minimizing method for data-driven elasticity with adaptive hyperparameters ⋮ Reducing internal variables and improving efficiency in data-driven modelling of anisotropic damage from RVE simulations ⋮ Efficient multiscale modeling of heterogeneous materials using deep neural networks



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