08 مهر 1401
غلامحسين روشني

غلامحسین روشنی

مرتبه علمی: دانشیار
نشانی:
تحصیلات: دکترای تخصصی / مهندسی هسته ای
تلفن:
دانشکده: دانشکده انرژی

مشخصات پژوهش

عنوان
Prediction of optimum gas mixture forhighest SXR intensity emitted by a 4kJ plasma focus device using artificial neural network
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
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پژوهشگران مرتضی حبیبی (نفر اول)، اصغر سجاد نژاد (نفر دوم)، عباس رضایی (نفر سوم)، محسن افشار منش (نفر چهارم)، غلامحسین روشنی (نفر پنجم)

چکیده

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.