RE-MAKE doctoral candidate Mohammad Reza Mehraban (DC9) represented the project at the ESIAM26 conference in Vicenza, Italy. His presentation introduced a mesh-based numerical framework designed to predict the morphology of cold spray deposits. The methodology employs an inverse model to calibrate physical parameters against experimental deposition profiles. Additionally, he showcased a machine-learning-based surrogate model for 2D shape prediction, developed to facilitate the integration of optimization algorithms into toolpath planning for additive manufacturing.
