Prediction of Optimum Gas Mixture for Highest SXR Intensity Emitted by a 4kj Plasma Focus Device Using Artificial Neural Network
Authors/Creators
- 1. Plasma and Fusion Research School, Nuclear Science and Technology Research Institute, Tehran, Iran,Energy Faculty, Kermanshah University of Technology.
- 2. Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
- 3. Plasma and Fusion Research School, Nuclear Science and Technology Research Institute, Tehran, Iran
- 4. Energy Faculty, Kermanshah University of Technology
- 5. Electrical Engineering Department, Kermanshah University of Technology, Kermanshah, Iran
Description
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.
Files
228-Article Text-1164-3-10-20151012.pdf
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