Application programming interface for electron beam welding of Inconel 718 thin plates

Abstract

In this paper the simulation of electron beam welding of Inconel 718 thin plates by a moving linear heat source is considered. Neural network models are developed and used for the description of the dependence of the molten pool geometry characteristics on the process parameters - electron beam power, welding velocity, and the plate thickness. Neural network models, based on a multi-layered feedforward neural network, trained with Levenberg-Marquardt error backpropagation algorithm are compared with estimated regression models. The neural networks are trained, tested and validated using a set of experimental data. The resulting models are implemented for developing of an application programming interface for electron beam welding of Inconel 718 thin plates, which is used for prediction, investigation and graphical optimization of the molten pool geometry characteristics of the obtained electron beam welds.