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Characterization of bubbles in gas–liquid multiphase flow is important to design and optimize industrial systems. Visual techniques have been developed including image processing to measure bubble size distributions. However, traditional image processing methods have significantly influenced on experimental settings. Thus, an improved bubbled detection method based on convolutional neural networks (CNN) was proposed in this work. The method uses a faster region-based CNN (Faster RCNN) to detect the bubble location, and a pixel classification network to segment bubble shapes. The experiments were conducted using three types of bubble generators with various background intensities and volume flow rates. Also, the back-bone CNN architectures used on Faster RCNN and the pixel classification network were compared. The model network was capable of characterizing the bubble information in real-time and had potential to replace the traditional image processing method with high versatility.
Recently, an air-lift bio-reactor operated by micro bubbles has been utilized to product hydrogen fuel. To enhance the performance, characteristics of hydrodynamics inside the bio-reactor were analyzed using a numerical simulation for two-phase flow. An Eulerian model was employed for both of liquid and gas phases. The standard k-ε model was used for turbulence induced by micro bubbles. A Population Balance Model was employed to consider size distribution of bubbles. A hollow cylinder was introduced at the center of the reactor to reduce a dead area which disturbs circulation of CO bubbles. An appropriate diameter of the draft tube and hollow cylinder were optimized for better performance of the bio-reactor. The optimum model could be obtained when the cross-sectional area ratio of the hollow cylinder to the reactor, and the width ratio of the riser to the downcomer approached 0.4 and 3.5, respectively. Consequently, it is expected that the optimum model could enhance the performance of the bio-reactor with the homogeneous distribution and higher density of CO, and more effective mixing.
The present work was done lo investigate the effectiveness of Kyo˘khach'ugotang and Ch'o˘ngp'och'ugotang, known to cure female genital disease caused by extravasated blood. The extracted powder of those two prescription were administered to experimental animals and effects on anti-inflammatory, anti-pyretic, analgesic, anti-microbial and anti-thrombose action were observed. The results obtained in this wort were summarized as follows: 1. The extracted powder the mixture of each extracted powder of Kyo˘khach'ugotang and Ch'o˘ngp'och'ugotang showed more significant anti-inflammatory effect than control group. 2. The extracted powder and the mixture of each extracted powder of both prescriptions showed more significant anti-pyretic effect than control group. 3. Significant analgesic effect was recognized in the extracted powder and the mixture of each extracted powder of both prescriptions. Especially, the extracted powder of Kyo˘khach'ugotang showed more significant effect than another. 4. Upon the degree of concentration of FDP, the extracted powder, the mixture of each extracted powder of Kyo˘khach'ugotang and the extracted powder of Ch'o˘ngp'och'ugotang showed significant effect of rupture of extravasated blood. 5. Anti-microbial effect of both prescriptions against Staphylococcus aureus, Bacillus subtilis was observed, especially in the Staphylococcus aureus was remarkable in the effect. It is thought to be valuable on the therapy of pyogenic stapylococcal inflammation. By the above results, anti-inflammatory, anti-pyretic, analgesic, anti-microbial and anti-thrombose action were recognized, and by comparison of both prescriptions, Kyo˘khach'ugotang showed siginficant effect on the analgesic action, the degree of concentration of FDP and Ch'o˘ngp'och'ugotang was remarkable anti-pyretic effect but others were not any marked difference. In addition to the above resultls, the extracted powders of Kyo˘khach'ugotang and Ch'o˘ngp'och'ugotang showed better effects, than the mixture of each extracted powders, but not remakable significant.