12 مهر 1401
غلامحسين روشني

غلامحسین روشنی

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

مشخصات پژوهش

عنوان
Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
oil products monitoring; neural network; X-ray spectrum; MCNP code
پژوهشگران غلامحسین روشنی (نفر اول)، پیشه وا جمال محمد علی (نفر دوم)، شیوان محمد (نفر سوم)، رابرت هنوس (نفر چهارم)، لقمان عبدالکریم (نفر پنجم)، عدنان الانزی (نفر ششم به بعد)، محمدامیر ستاری (نفر ششم به بعد)، صبا امیری (نفر ششم به بعد)، احسان ناظمی (نفر ششم به بعد)، احسان افتخاری زاده (نفر ششم به بعد)، مصطفی کالمون (نفر ششم به بعد)

چکیده

Radiation-based instruments have been widely used in petrochemical and oil industries to monitor liquid products transported through the same pipeline. Different radioactive gamma-ray emitter sources are typically used as radiation generators in the instruments mentioned above. The idea at the basis of this research is to investigate the use of an X-ray tube rather than a radioisotope source as an X-ray generator: This choice brings some advantages that will be discussed. The study is performed through a Monte Carlo simulation and artificial intelligence. Here, the system is composed of an X-ray tube, a pipe including fluid, and a NaI detector. Two-by-two mixtures of four various oil products with different volume ratios were considered to model the pipe’s interface region. For each combination, the X-ray spectrum was recorded in the detector in all the simulations. The recorded spectra were used for training and testing the multilayer perceptron (MLP) models. After training, MLP neural networks could estimate each oil product’s volume ratio with a mean absolute error of 2.72 which is slightly even better than what was obtained in former studies using radioisotope sources.