Material modeling using modern numerical methods accelerates the design process and
reduces the costs of developing new products. However, for multiscale modeling of
heterogeneous materials, the well-established homogenization techniques remain
computationally expensive for high accuracy levels. In this talk, a machine learning approach
is proposed as a computationally efficient solution method that is capable of providing a high
level of accuracy.
