An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks
(2020)
Journal Article
Yan, S., Zou, X., Ilkhani, M., & Jones, A. (2020). An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks. Composites Part B: Engineering, 194, https://doi.org/10.1016/j.compositesb.2020.108014
© 2020 Elsevier Ltd Modelling of the progressive damage behaviour of large-scale composite structures presents a significant challenge in terms of computational cost. This is due to the detailed description in finite element (FE) models for the mater... Read More about An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks.