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Title
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Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products
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Type
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JournalPaper
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Keywords
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oil products monitoring; neural network; X-ray spectrum; MCNP code
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Abstract
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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.
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Researchers
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El Mostafa Kalmoun (Not In First Six Researchers), Ehsan Eftekhari zadeh (Not In First Six Researchers), Ehsan Nazemi (Not In First Six Researchers), saba Amiri (Not In First Six Researchers), MohammadAmir Sattari (Not In First Six Researchers), Adnan Alhathal Alanezi (Not In First Six Researchers), Lokman Abdulkareem (Fifth Researcher), Robert Hanus (Fourth Researcher), shiavn mohammed (Third Researcher), Peshawa Jammal Muhammad Ali (Second Researcher), Gholam Hossein Roshani (First Researcher)
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