Outputs (13)

Exploring the Elastic Properties of Woven Fabric Composites: A Machine Learning Approach for Improved Analysis and Design (2023)
Presentation / Conference Contribution
Hayat, K., Ullah, Z., Siddique, S., & Ahmad, Z. (2023, May). Exploring the Elastic Properties of Woven Fabric Composites: A Machine Learning Approach for Improved Analysis and Design. Presented at 1st International Conference on Modern Technologies in Mechanical & Materials Engineering (MTME-2023), Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan

Woven fabric reinforced plastic composites are highly favoured in the aerospace and automotive industries for their exceptional impact resistance and ease of manufacture. To design and analyse these structures, it is crucial to determine their elasti... Read More about Exploring the Elastic Properties of Woven Fabric Composites: A Machine Learning Approach for Improved Analysis and Design.

Comprehensive inter-fibre failure analysis and failure criteria comparison for composite materials using micromechanical modelling under biaxial loading (2023)
Journal Article
Wan, L., Ullah, Z., Yang, D., & Falzon, B. G. (2023). Comprehensive inter-fibre failure analysis and failure criteria comparison for composite materials using micromechanical modelling under biaxial loading. Journal of Composite Materials, 57(18), 2919-2932. https://doi.org/10.1177/00219983231176609

Inter-fibre failure analysis of carbon fibre-reinforced polymer (CFRP) composites, under biaxial loading conditions, has been a longstanding challenge and is addressed in this study. Biaxial failure analysis of IM7/8552 CFRP unidirectional (UD) compo... Read More about Comprehensive inter-fibre failure analysis and failure criteria comparison for composite materials using micromechanical modelling under biaxial loading.

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.