supported by the Natural Science Foundation of Chongqing(CSTB2022NSCQ-MSX0296);Strategic Priority Research Program of the Chinese Academy of Sciences(XDC06030102);National Key R&D Program of China(2020YFA0713603);National Natural Science Foundation of China(12271409).
Constitutive modeling of heterogeneous hyperelastic materials is still a challenge due to their complex and variable microstructures.We propose a multiscale datadriven approach with a hierarchical learning strategy fo...