August 9, 2022
Gholam Hossein Roshani

Gholam Hossein Roshani

Academic rank: Associate professor
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Education: Ph.D in Nuclear Engineering
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Faculty: Faculty of energy

Research

Title
Prediction of optimum gas mixture forhighest SXR intensity emitted by a 4kJ plasma focus device using artificial neural network
Type Article
Keywords
Researchers Morteza Habibi، Asghar Sadighzadeh، Abbas Rezaei، Mohsen Afsharmanesh، Gholam Hossein Roshani

Abstract

In this study, artificial neural network (ANN) is investigated to predict the optimum gas mixture for highest soft X-ray (SXR) intensity emitted by a 4kJ plasma focus device. To do this multi-layer perceptron (MLP) neural network is used for developing the ANN model in MATLAB 7.0.4 software. In this model, the input parameters are voltage, Percentage of nitrogen in admixture and pressure and the output is SXR intensity. The obtained results show that the proposed ANN model has achieved good agreement with the experimental data and has a small error between the estimated and experimental values. Therefore, this model is a useful, reliable, fast and cheap tool to predict the optimum gas mixture for highest SXR intensity emitted by plasma focus devices.