Interfacial-tension-force model for the wavy stratified liquid-liquid flow pattern transition: The usage of two different approaches

Abstract Flow pattern is an important engineering design factor in two-phase flow in the chemical, nuclear and energy industries, given its effects on pressure drop, holdup, and heat and mass transfer. The prediction of two-phase flow patterns through phenomenological models is widely used in both industry and academy. In contrast, as more experimental data become available for gas-liquid flow in pipes, the use of data-driven models to predict flow-pattern transition, such as machine learning, has become more reliable. This type of heuristic modeling has a high demand for experimental data, which may not be available in some industrial applications. As a consequence, it may fail to deliver a sufficiently generalized transition prediction. Incorporation of physics in machine learning is being proposed as an alternative to improve prediction and also to reduce the demand for experimental data. This paper evaluates the use of hybrid-physics-data machine learning to predict gas-liquid flow-pattern transition in pipes. Random forest and artificial neural network are the chosen tools. A database of experiments available in the open literature was collected and is shared in this work. The performance of the proposed hybrid model is compared with phenomenological and data-driven machine learning models through confusion matrices and graphics. The results show improvement in prediction performance even with a low amount of data for training. The study also suggests that graphical comparison of flow-pttern transition boundaries provides better understanding of the performance of the models than the traditional metric

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On the effect of viscosity on stability of stratified gas—liquid flow—application to flow pattern transition at various pipe inclinations

Chemical Engineering Science ◽

10.1016/0009-2509(91)80170-4 ◽

1991 ◽

Vol 46 (8) ◽

pp. 2123-2131 ◽

Cited By ~ 43

Author(s):

Dvora Barnea

Keyword(s):

Flow Pattern ◽

Liquid Flow ◽

Flow Pattern Transition ◽

Gas Liquid Flow

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Liquid flow pattern transition, droplet diameter and size distribution in the cavity zone of a rotating packed bed: A visual study

Chemical Engineering Science ◽

10.1016/j.ces.2016.10.044 ◽

2017 ◽

Vol 158 ◽

pp. 429-438 ◽

Cited By ~ 49

Author(s):

Le Sang ◽

Yong Luo ◽

Guang-Wen Chu ◽

Jing-Peng Zhang ◽

Yang Xiang ◽

...

Keyword(s):

Flow Pattern ◽

Size Distribution ◽

Liquid Flow ◽

Droplet Diameter ◽

Packed Bed ◽

Visual Study ◽

Rotating Packed Bed ◽

Flow Pattern Transition

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Effects of Density and Viscosity in Vertical Zero Net Liquid Flow

Journal of Energy Resources Technology ◽

10.1115/1.483161 ◽

2000 ◽

Vol 122 (2) ◽

pp. 49-55 ◽

Cited By ~ 3

Author(s):

Hyoung-Jin An ◽

Julius P. Langlinais ◽

S. L. Scott

Keyword(s):

Flow Pattern ◽

Liquid Flow ◽

Petroleum Industry ◽

Flow Distribution ◽

Liquid Holdup ◽

Cylindrical Cyclone ◽

Flow Pattern Transition ◽

Transition Criteria ◽

Superficial Gas Velocity ◽

Effects Of Density

An experimental study was conducted to investigate the effects of density and viscosity on zero net liquid flow (ZNLF) in vertical pipes. Predicting liquid holdup under ZNLF conditions is necessary in several types of petroleum industry operations. These include predicting bottomhole pressures in pumping oil wells and the design of compact gas-liquid cylindrical cyclone (GLCC©)1 separators. Models are proposed to predict flow pattern transitions under ZNLF conditions and comparisons are made with commonly used vertical flow pattern transition criteria. Data was collected using a 3-in.-diam, 14-ft-section of transparent vertical pipe. Several different fluids, of differing density and viscosity, were utilized with air flowing at approximately 25 psig. Results are presented showing the liquid holdup and the flow distribution coefficient C0 as a function of density, viscosity, and superficial gas velocity. [S0195-0738(00)00402-7]

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