7 research outputs found
Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter
Evaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline\u2019s scale layer thickness
Feasibility study of using X-ray tube and GMDH for measuring volume fractions of annular and stratified regimes in three-phase flows
Proposing a nondestructive and intelligent system for simultaneous determining flow regime and void fraction percentage of gas-liquid two phase flows using polychromatic X-ray transmission spectra
Simulation study of utilizing X-ray tube in monitoring systems of liquid petroleum products
Simulation Study of Utilizing X-ray Tube in Monitoring Systems of Liquid Petroleum Products
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