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- W4313172322 abstract "Abstract The volume fraction percentage measurement in multiphase flows is a vital need in the oil, gas and petroleum industries. Thus, diverse and precise techniques should be presented for achieving this purpose. In this research, the water-oil two-phase flows were simulated using the MCNPX code in operational and real conditions in the oil district of Kharg. A single source 137 Cs and a NaI (Tl) detector were used to provide the required data for volume fraction prediction. Then, the ANN, Gaussian, Linear Regression, and Fourier techniques were applied to the acquired nuclear data in order to compare and identify the suitable and precise method for predicting the volume fraction. Using the ANN, Gaussian, Linear Regression, and Fourier techniques, the volume fraction was predicted with a mean relative error percentage of less than 8.71, 10.14, 16.07, and 12.45%, respectively. Also, the root mean square error quantities were calculated 1.05, 1.18, 1.36, and 1.27, respectively. The results reveal that the ANN method has superior in comparison with the other methods." @default.
- W4313172322 created "2023-01-06" @default.
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- W4313172322 date "2022-10-10" @default.
- W4313172322 modified "2023-10-16" @default.
- W4313172322 title "Evaluation of nuclear data analysis techniques for volume fraction prediction in the flow meter" @default.
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- W4313172322 doi "https://doi.org/10.1515/ract-2022-0043" @default.
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