All Outputs (3)

Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling (2023)
Journal Article
Wan, L., Ullah, Z., Yang, D., & Falzon, B. G. (2023). Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling. Composite Structures, 312, Article 116837. https://doi.org/10.1016/j.compstruct.2023.116837

This study presents a data-driven, probability embedded approach for the failure prediction of IM7/8552 unidirectional carbon fibre reinforced polymer (CFRP) composite materials under biaxial stress states based on micromechanical modelling and artif... Read More about Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling.

A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites (2022)
Journal Article
Wan, L., Sheng, Y., McCarthy, E. D., & Yang, D. (2023). A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites. Engineering Fracture Mechanics, 277, Article 108982. https://doi.org/10.1016/j.engfracmech.2022.108982

This study proposed a novel approach based on the 3D discrete element method (DEM) to simulate the progressive delamination in unidirectional carbon fibre reinforced polymer (CFRP) composite laminates. A hexagonal packing strategy was used for modell... Read More about A novel approach for 3D discrete element modelling the progressive delamination in unidirectional CFRP composites.

A micromechanics and machine learning coupled approach for failure prediction of unidirectional CFRP composites under triaxial loading: A preliminary study (2021)
Journal Article
Chen, J., Wan, L., Ismail, Y., Ye, J., & Yang, D. (2021). A micromechanics and machine learning coupled approach for failure prediction of unidirectional CFRP composites under triaxial loading: A preliminary study. Composite Structures, 267, Article 113876. https://doi.org/10.1016/j.compstruct.2021.113876

This study presents a hybrid method based on artificial neural network (ANN) and micro-mechanics for the failure prediction of IM7/8552 unidirectional (UD) composite lamina under triaxial loading. The ANN is trained offline by numerical data from a h... Read More about A micromechanics and machine learning coupled approach for failure prediction of unidirectional CFRP composites under triaxial loading: A preliminary study.