12 مهر 1401
غلامحسين روشني

غلامحسین روشنی

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

مشخصات پژوهش

عنوان
Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
GMDH neural networks;X-ray tube;Flow pattern;Volume fraction;Gas-oil–water;Three phase flow
پژوهشگران م. روشنی (نفر اول)، گیانگ فان (نفر دوم)، غلامحسین روشنی (نفر سوم)، رابرت هنوس (نفر چهارم)، بهروز ناظمی (نفر پنجم)، انریکو کورنیانی (نفر ششم به بعد)، احسان ناظمی (نفر ششم به بعد)

چکیده

In this investigation, a fan-beam photon attenuation based system, including one X-ray tube and two sodium iodide crystal detectors, combined with group method of data handling (GMDH) neural network is proposed to recognize type of flow regime and predict gas-oil–water volume fractions of a three phase flow. One GMDH neural network was considered for recognizing flow patterns and two GMDH networks were implemented to predict the volume fractions. The recorded photon energy spectra from the two sodium iodide detectors were defined as the inputs of the three GMDH neural networks. The type of flow pattern and volume fractions were the output obtained from the first and the other two GMDH neural networks, respectively. Through the application of the proposed methodology, all of the flow patterns were recognized correctly except one single case. The volume fraction was also predicted with RMS error of less than 3.1.