Abstract

A unique device, namely as the microbubble generator is a device which is able to maintain more dissolved oxygen inside the water for various purposes including waste water treatment and aquaculture with less energy consumption. One of that types is a venturi-porous pipe microbubble generator. It has the advantages of simple construction and easy to maintain. The purpose of the present study was to investigate the performance of venturi-porous pipe microbubble generator. The developed microbubble generator was a venturi-porous pipe type with inlet angle of 20°, outlet angle of 12°, and inlet-throat diameter ratio (Din/Dt) of 2.5. The experiments were conducted under an adiabatic condition in various air flow rates (QG) of 0.2 lpm to 1.0 lpm and water flow rates (QL) of 30 lpm to 80 lpm. The device was located in the depth of 20 cm from water surface in a glass aquarium with the dimension of 280 cm × 60 cm × 40 cm. To investigate the microbubble behaviors, a high speed video camera was used. A watershed algorithm of a digital image processing technique was implemented to proceed the captured images of microbubbles. Moreover, a pressure transducer recorded the inner pressure of inside the microbubble generator in order to calculate hydraulic power (LW) and bubble generating efficiency (ηB). Disolved Oxygen (DO) was also measured in the point of 60 cm and 180 cm from microbubble generator nozzle tip to determine volumetric oxygen mass transfer coefficient (KLa). As the result, performance of the microbubble was influenced by air and water flow rates. Under a constant QG, the mean bubble diameter reduced as the QL increased. Results from image processing showed that size of the microbubbles was distributed in uni-modal peaked PDF curve. Hydraulic power was significantly influenced by QL whereas bubble generating efficiency decreased as the QL increased. The KLa value decreased as the increase of distance from microbubble nozzle. Results from the present work can be used to validate the available CFD simulation models.

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