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- W2297672272 abstract "The development of advanced nuclear reactor conceptions depends largely on the amount of availabledata to the designer. Non invasive ultrasonic techniques can contribute to the evaluation of gas-liquidtwo-phase regimes in the nuclear thermo-hydraulic circuits. A key-point for success of thosetechniques is the interpretation of the ultrasonic signal. In this work, a methodology based in artificialneural networks (ANN) is proposed to predict size distribution of bubbles in a bubbly flow. Toaccomplish that, an air feed system control was used to obtain specific bubbly flows in anexperimental system utilizing a Plexiglas vertical bubbly column. Four different size distribution ofbubbles were generated. The bubbles were photographed and measured. To evaluate the different sizedistribution of bubbles it was used the ultrasonic reflected echo on the opposite wall of the column.Then, an ANN has been developed for predicting size distribution of bubbles by using the frequencyspectra of the ultrasonic signal as input. A trained artificial neural network using ultrasonic signal inthe frequency domain can evaluate with a good precision the size distribution of bubbles generated inthis system." @default.
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- W2297672272 date "2011-01-01" @default.
- W2297672272 modified "2023-10-10" @default.
- W2297672272 title "Determination of size distribution of bubbles in a bubbly column two-phase flows by ultrasound and neural networks" @default.
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