Scheduled presentations:

• Keynote Original Eigenstrain Framework Combined with Machine Learning for Fast Residual Stress and Distortion Prediction in LPBF Parts
  *P. Markovic (Empa/ETHZ), E. Mazza (Empa/ETHZ), E. Hosseini (Empa)
• Reduced Order Model for Temperature Field Simulation of Wire Arc Additive Manufacturing
  *D. Strobl (Bundesanstalt für Materialforschung und (BAM)), J. Unger (Bundesanstalt für Materialforschung und (BAM)), C. Ghnatios (Arts et Métiers institute of technology,HESAM), A. Pittner (Bundesanstalt für Materialforschung und (BAM)), M. Rethmeier (IWF, Technische Universität Berlin), A. Robens-Radermacher (Bundesanstalt für Materialforschung und (BAM))
• Fast Thermal History Prediction During Additive Manufacturing Processes Using Deep Learning Methodologies
  *L. Salesses (Cenaero), L. Arbaoui (Cenaero), A. François (Cenaero), C. Sainvitu (Cenaero)
• Accelerated Additive Manufacturing Simulation Through Inherent Strains Meta-Models Trained With Generic Databases
  *H. Hernandez (Cenaero), N. Poletz (Cenaero), T. Van Hoof (Cenaero)
• Data-driven surrogate modelling of residual stresses in Laser Powder-Bed Fusion
  *L. Lestandi (Ecole Centrale Nantes), J. Wong (IHPC, A*star), G. Dong (UC Denver), M. Jhon (IHPC, A*Star)