In-flight and upon impact particle characteristics modelling in plasma spray process

Artificial neural networks was trained and optimized to establish the relationships linking in-flight particle average diameter and process parameters to in-flight particle average velocity and surface temperature. Then, the established ANN relationships permitted to determine the in-flight particle average velocity and surface temperature versus their diameter for given process parameters. These predicted average velocity and surface temperature data were then used to determine the time for complete melting of the particle and its dwell-time before impact by an analytical model for given operating conditions.