Despite advancements in predicting the constitutive relationships of composite materials,
characterizing the effects of microstructural randomness on their mechanical behaviors …

This review paper presents an overview of computational methods for modelling the failure
of composite materials, with a focus on fracture modelling. The paper begins by discussing …

Elastomers are made of chain-like molecules to form networks that can sustain large
deformation. Rubbers are thermosetting elastomers that are obtained from irreversible …

This study presents data-driven reduced-order models (ROMs) of a lunar orbiter based on
principal component analysis (PCA) and artificial neural networks (ANNs) for a ground …

This study proposes an image composition technique based on convolutional neural
networks (CNNs) to construct a surrogate model for predicting fan plots of three-dimensional …

A spatiotemporal deep learning framework is proposed that is capable of two-dimensional
full-field prediction of fracture in concrete mesostructures. This framework not only predicts …

The complex modeling and computational cost are unavoidable in analysis of finite element
models (FEMs) when mechanical properties of woven composite materials are predicted. To …

Computational solid mechanics has become an indispensable approach in engineering,
and numerical investigation of fracture in composites is essential as composites are widely …

Investigating the mechanical behavior and damage patterns of ultra-thin-ply composite joints
is essential for ensuring their widespread application in the aerospace field. It is currently an …

This study employs diffusion generative models to reconstruct random representative
volume elements (RVEs) of unidirectional composites with noncircular fibers. Microscope …