Scheduled presentations:

• Determining Feasibility Bounds of Lamination Parameters using Neural Networks
  *S. Madabhushi Venkata (TUD)
• Machine Learning-Accelerated Predictions of Design Allowable of Composite Laminates
  *C. Furtado (FEUP), L. Rodrigues (FEUP), J. Ferreira (FEUP), I. Lopes (INEGI), J. Esteves (FEUP), F. Danzi (INEGI), G. Guillamet (BSC)
• A Data Driven Constitutive Model for the Elasto-Damage Response of Transversely Isotropic Materials
  *M. Kofler (TU Wien), L. Peyker (Luxner Engineering ZT GmbH), K. Key (TU Wien), C. Fricke (TU Wien), M. Luxner (Luxner Engineering ZT GmbH), H. Pettermann (TU Wien)
• Prediction of shear angles in molten state thermo-stamped thermoplastic composites using a graph neural network
  *B. Wintiba (Université libre de Bruxelles), C. Viviers (Eindhoven University of Technology), F. Caetano (Eindhoven University of Technology), J. Chevalier (Material Science Application Center), F. Van Der Sommen (Eindhoven University of Technology), T. Massart (Université libre de Bruxelles), P. Berke (Université libre de Bruxelles)
• From Material Sample to Statistically Representative Elastic Properties: an X-Ray CT-Based End-to-End Pipeline to Predict as-Manufactured Properties of 3D-Textile Reinforced Composites
  *J. Friemann (Chalmers University of Technology), L. Pilgaard Mikkelsen (Technical University of Denmark), C. Oddy (Chalmers University of Technolgy), M. Fagerström (Chalmers University of Technolgy)