Statistical Characterization of Bubble Breakup Flow Structures in Swirl-Type Bubble Generator Systems
Drajat Indah Mawarni(1*), Wibawa Endra Juwana(2), IGNB Catrawedarma(3), Kumara Ari Yuana(4), Wiratni Budhijanto(5), Deendarlianto Deendarlianto(6), Indarto Indarto(7)
(1) Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Gadjah Mada, Grafika 2 Street, Yogyakarta 55281, Indonesia
(2) Department of Mechanical Engineering, Faculty of Engineering, Universitas Sebelas Maret, Ir. Sutami Street No.36A, Surakarta, Indonesia
(3) Department of Mechanical Engineering, Politeknik Negeri Banyuwangi, Raya Jember Km. 13 Street, Labanasem, Banyuwangi 68461, Indonesia
(4) Computer Science Departement, Universitas Amikom Yogyakarta, Jl Raya Pajajaran, Ring Road Utara, Sleman, Yogyakarta, Indonesia
(5) Bioprocess Engineering Research Group, Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Grafika 2 Street, Yogyakarta 55281, Indonesia
(6) Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Gadjah Mada, Grafika 2 Street, Yogyakarta 55281, Indonesia
(7) Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Gadjah Mada, Grafika 2 Street, Yogyakarta 55281, Indonesia
(*) Corresponding Author
Abstract
The bubble breakup pattern on a swirl-type bubble generator (MBG) with water and air fluids was experimentally studied. The bubble breakup pattern was analyzed visually and characterized using several parameters such as Pressure Drop (∆P), Kolmogorov Entropy, Standard Deviation, and DWT (Discrete Wavelet Transform), which were taken from the extraction of pressure signals at the water inlet and outlet of the bubble generator. The wavelet spectrum of the measured signal was shown to identify the overall bubble breakup pattern, and the wavelet variance vector is proposed as a character vector to identify the bubble breakup pattern. The results show that there were three types of different flow breakup patterns: (1) static breakup, (2) dynamic breakup, and (3) tensile breakup. The observed bubble breakup sub-patterns can be categorized into tensile, moderate tensile, high tensile, dynamic, low dynamic, static, and high static sub-patterns. The static clustered breakup pattern has the highest wavelet energy compared to the tensile and dynamic clustered breakup.
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DOI: https://doi.org/10.22146/ajche.78558
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