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Dimensional analysis and scaling in two-phase gas–liquid stratified pipe flow–Methodology evaluation

26

Citations

7

References

2019

Year

Abstract

Multiphase flow models are validated by comparison with a relatively good supply of high-quality laboratory data, and a relatively sparse supply of field data, which tends to have poorer quality. One of the principal challenges for multiphase flow models, in terms of uncertainty, is the difference in scale and some of the fluid properties between field and laboratory conditions. Therefore, the models may become unreliable when they are applied to conditions that are very different from those in the laboratory. IFE (Institute for Energy Technology) has recently developed and demonstrated scale-up rules for the most basic multiphase pipe flows. The objective of the work presented in this paper was to select appropriate data from our existing database and design new, scaled laboratory experiments, well-suited to demonstrate (or test) the scaling rules by comparing the results. The data include fluid properties, pipe configurations and flow rates. Besides the observed flow pattern, liquid holdup and pressure gradient are the two main parameters for comparison. IFE's CO2 Flow Loop with a test section inner diameter (ID) of 44 mm, operates for two-phase flows over a large range of pressures and temperatures on the equilibrium line of pure CO2. In order to verify scale-up principles, series of experiments were conducted according to the scaling rules to simulate similar conditions. The experiments were performed with gas–liquid two-phase CO2 for fully-developed, steady-state flow, in a horizontal or near-horizontal pipe. The flow regimes include stratified and annular flows. The experimental results showed that measurements of liquid holdup, and pressure gradient in the CO2 Flow Loop are in excellent agreement with appropriately scaled data from the larger-scale facilities. The results also confirm that the gas-to-liquid density ratio plays an important role. The experiments provide valuable data sets for verifying scaling laws, which are lacking in the literature.

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