Shape control in solid state additive manufacturing

Among the many qualities of Cold Spray, its ability to create large and thick deposits with a wide range of materials and limited temperature effects has made it a highly promising technology for Additive Manufacturing. Accurately predicting the shape of the deposits and its correlation to working parameters is a key enabler for its future developments, as geometry control is currently one of its main hindrances. We are working by combining physics-based and machine learning approaches to develop comprehensive and computationally efficient shape prediction models for Cold Spray Additive Manufacturing, while concurrently optimizing the tool trajectory towards superior geometrical accuracy.