AI RESEARCH
Machine Learning Surrogate Modeling for Homogenization of Hyperelastic Materials with Boolean Microstructures
arXiv CS.LG
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ArXi:2606.00938v1 Announce Type: cross Data-driven surrogate models are an alternative to numerical homogenization of heterogeneous materials. In this contribution, a supervised learning approach is presented for predicting effective Lam\'e parameters of hyperelastic composites from low-dimensional microstructural descriptors.