Determination of size distribution of bubbles in a bubbly column two-phase flows by ultrasound and neural networks

摘要

The development of advanced nuclear reactor conceptions depends largely on the amount of availableuddata to the designer. Non invasive ultrasonic techniques can contribute to the evaluation of gas-liquidudtwo-phase regimes in the nuclear thermo-hydraulic circuits. A key-point for success of thoseudtechniques is the interpretation of the ultrasonic signal. In this work, a methodology based in artificialudneural networks (ANN) is proposed to predict size distribution of bubbles in a bubbly flow. Toudaccomplish that, an air feed system control was used to obtain specific bubbly flows in anudexperimental system utilizing a Plexiglas vertical bubbly column. Four different size distribution ofudbubbles were generated. The bubbles were photographed and measured. To evaluate the different sizeuddistribution of bubbles it was used the ultrasonic reflected echo on the opposite wall of the column.udThen, an ANN has been developed for predicting size distribution of bubbles by using the frequencyudspectra of the ultrasonic signal as input. A trained artificial neural network using ultrasonic signal inudthe frequency domain can evaluate with a good precision the size distribution of bubbles generated inudthis system.