کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5001757 1461081 2017 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Intelligent densitometry of petroleum products in stratified regime of two phase flows using gamma ray and neural network
ترجمه فارسی عنوان
دانسیتومتری هوشمند محصولات نفتی در حالت کلاسیک جریان دو فاز با استفاده از پرتو گاما و شبکه عصبی
کلمات کلیدی
کشش سنجی، فرآورده های نفتی، اشعه گاما، ابزار تابش، شبکه های عصبی مصنوعی،
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی
Radiation based instruments in the petroleum industry are usually utilized to measure the volume fraction and flow regime type of multiphase flows in stable conditions. But in unstable conditions (when the temperature and pressure could change in pipelines), in addition to mentioned parameters, online measuring the density of liquid phase is of great importance. In this work, a combination of dual modality densitometry technique and artificial neural network (ANN) was used in order to predict the density of liquid phase in the stratified regime of gas-liquid two phase flows. In the first step, a Monte Carlo simulation model was used to obtain the optimum position for the scattering detector in dual modality densitometry configuration. At the next step, an experimental setup was designed based on obtained optimum positions for detectors from simulation to generate the required data for training and testing the ANN. Applying this novel method, density of liquid phase was predicted with the mean relative error (MRE) of less than 0.1243% in the stratified regime of gas-liquid two phase flows for void fractions in the range of 10-70%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Flow Measurement and Instrumentation - Volume 58, December 2017, Pages 6-11
نویسندگان
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