A methodology for direct parameter identification for experimental results using machine learning—Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science, (244):113274, Elsevier, 2024. [PUMA: topic_engineering area_architectures FRP using experimental deformation direct learning application identification world parameter machine Real results highly non-linear behavior]
A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters. Journal of Composites Science, (6)10:318, MDPI, 2022. [PUMA: topic_engineering 3D Approach Characterisation Composites Data Deformation Dependent Driven Experimental Failure Fibre Modelling Rate Reinforced Shear Strain Thermoplastic]