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Prediction of Slug Frequency for Gas-Liquid Flows

Authors: G. J. Zabaras;

Prediction of Slug Frequency for Gas-Liquid Flows

Abstract

Abstract During slug flow, knowledge of the slug frequency is essential for the gas -liquid receiving facility design as well as for predicting various slug flow characteristics such as slug length and pressure drop. Various methods proposed in the literature for predicting the slugging frequency in horizontal and inclined pipes were examined. These included both empirical correlations as well as mechanistic models. Slug flow frequency data taken with an air-water system in a laboratory flow loop together with data from the published literature were compared to the predictions of the various methods. A total of 399 data points were collected covering pipe diameters from 1 to 8 inches and inclinations from 0 to 11 degrees above the horizontal. A total of eight published methods were compared to the data but none was found satisfactory. For this reason, the mechanistic slug frequency model of Taitel and Dukler (1976) was investigated in detail as an alternative unbiased prediction method. This model required the solution of the unsteady-state equations for mass and momentum by a finite difference technique. This numerical model gave satisfactory results at the expense of considerable computer CPU time. For faster slug frequency calculations a new correlation was developed utilizing all 399 data points. This resulted in 0% average error (bias) and 60% average absolute error. This correlation represents a significant improvement in slug frequency prediction accuracy over the other methods studied.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
72
Top 10%
Top 10%
Average
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