Project description
New models enhance the design of robust printed composites
Additive manufacturing and automated fibre placement processes gave rise to a new class of fibre-reinforced materials – the variable angle tow (VAT) composites. VAT placement allows fibre orientations to change with position over the entire ply plane, resulting in varying stiffness properties. This allows the creation of tailored composite designs in terms of stiffness and buckling resistance. However, preserving fibre integrity requires the right combination of temperature, velocity, curvature radii and pressure during the printing process. To address this, the EU-funded PRE-ECO project will develop new models to describe VAT composites from a fibre-matrix to a component scale, and new machine learning models for defect identification. PRE-ECO’s new methods will significantly help reduce composite structural failures during the printing process.
Fields of science
- natural sciencescomputer and information sciencesdata science
- engineering and technologymaterials engineeringcomposites
- engineering and technologymechanical engineeringmanufacturing engineeringadditive manufacturing
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting Grant
Host institution
10129 Torino
Italy
See on map
Beneficiaries (1)
10129 Torino
See on map