Determination of the Half-Beam cone angle for Pierce electron gun design using an artificial neural network

Various electron gun design methods, especially iterative and noniterative, are generally utilized for preliminary electron gun design based on the input design beam parameters. In the electron gun design methods, calculating the half-beam cone angle is crucial, as it significantly influences the determination of the electron gun’s geometry. In this paper, an Artificial Neural Network (ANN) model was proposed for predicting the half-beam cone angle. The ANN model was trained and tested using experimental data obtained from previously documented studies on electron guns. The predicted results of the proposed ANN model were compared with three well-known methods in the electron gun design: iterative method, noniterative method, and modified noniterative method. The comparison indicates that the proposed ANN model achieves better performance than the other methods, with a Main Relative Error (MRE) of less than 5%.