Bubble measurement has been widely discussed in the literature and comparison studies have been widely performed to validate the results obtained for various forms of bubble size inferences. This paper explores three methods used to obtain a bubble size distribution—optical detection, laser diffraction and acoustic inferences—for a bubble cloud. Each of these methods has advantages and disadvantages due to their intrinsic inference methodology or design flaws due to lack of specificity in measurement. It is clearly demonstrated that seeing bubbles and hearing them are substantially and quantitatively different. The main hypothesis being tested is that for a bubble cloud, acoustic methods are able to detect smaller bubbles compared to the other techniques, as acoustic measurements depend on an intrinsic bubble property, whereas photonics and optical methods are unable to “see” a smaller bubble that is behind a larger bubble. Acoustic methods provide a real-time size distribution for a bubble cloud, whereas for other techniques, appropriate adjustments or compromises must be made in order to arrive at robust data. Acoustic bubble spectrometry consistently records smaller bubbles that were not detected by the other techniques. The difference is largest for acoustic methods and optical methods, with size differences ranging from 5–79% in average bubble size. Differences in size between laser diffraction and optical methods ranged from 5–68%. The differences between laser diffraction and acoustic methods are less, and range between 0% (i.e., in agreement) up to 49%. There is a wider difference observed between the optical method, laser diffraction and acoustic methods whilst good agreement between laser diffraction and acoustic methods. The significant disagreement between laser diffraction and acoustic method (35% and 49%) demonstrates the hypothesis, as there is a higher proportion of smaller bubbles in these measurements (i.e., the smaller bubbles ‘hide’ during measurement via laser diffraction). This study, which shows that acoustic bubble spectrometry is able to detect smaller bubbles than laser diffraction and optical techniques. This is supported by heat and mass transfer studies that show enhanced performance due to increased interfacial area of microbubbles, compared to fine bubbles.
This paper presents a computational model for microbubble enhanced performance of an airlift bioreactor (ALB). Five different bubble diameters were defined in the model under the same conditions (440 µm to 1 mm bubble diameter). The computational model parameters and the size of the ALB were defined by referring to experimental work done previously. The main objective of the model is to study the effect of bubble size on the rising velocity and the liquid flow velocity in the airlift reactor (ALB). The results obtained from the computational model shows that microbubbles have a better performance over larger bubbles because microbubbles have better gas hold up due to slow rise velocity and are able to increase the flow velocity due to their high surface area to volume ratio.
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