KARAKTERISTIK POLA ALIRAN DUA FASE GAS-CAIRAN NON-NEWTONIAN DI DALAM MICROCHANNELS BERPENAMPANG PERSEGI

Authors

  • Haslinda Kusumaningsih Universitas Gadjah Mada
  • M. Rian Alif Madani Universitas Gadjah Mada
  • Muhammad Fakhri Alfath Universitas Gadjah Mada
  • Aldy Franstanata Ritonga Universitas Gadjah Mada
  • Deendarlianto Deendarlianto Universitas Gadjah Mada
  • Indarto Indarto Universitas Gadjah Mada

DOI:

https://doi.org/10.21776/jrm.v13i2.1293

Keywords:

Flow Pattern, Two Phase Flow, Non-Newtonian, Pressure Drop, Image Processing, Void Fraction

Abstract

The aim of this study is to investigate the characteristics of gas-non-Newtonian liquids flow patterns in square microchannels. The microchannels  that used in this study was made by acrylic material with horizontal orientation and the side length of 8x10-4 m. Water, Air, Carboxymethyl Cellulose 0.2%wt (CMC 0.2%wt) aquoeus solution,  and Xanthan Gum 0.2%wt (XG 0.2%wt) aquoeus solution were used in this study as the liquid test. Moreover, nitrogen gas was used as gas test. The liquid superficial velocity was varied of 0.1-1 m/s. Then, the  gas superficial velocity variation of 0.26-7.8 m/s.  The differential pressure transducer was used in this study to measure the pressure drop, which is occurs in square microchannels. Whereas, The flow patterns were recorded by using the high-speed camera. Furthermore the flow pattern video was analyzed by using image processing method  to obtain the flow pattern charcteristics. The two-phase flow pressure drop of all gas-Newtonian/non-Newtonian liquids two-phase flows in this study increase by increasing JL in the same JG. The flow patterns that occur in this study are bubbly, slug, slug-annular and churn. The viscosity and rheological parameter of liquids test influenced the characteristic of flow patterns.  The flow patterns in this study were plotted in the flow patterns map and suitable with the flow patterns transisiton lines based on the previous study. Likewise, the experimental pressure drop shows the good agreement with the pressure drop prediction correlation by Kawahara et al. (2011).

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Published

2022-08-31

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