2019
DOI: 10.2516/ogst/2019034
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Probabilistic approach of a flow pattern map for horizontal, vertical, and inclined pipes

Abstract: A way to predict two-phase liquid-gas flow patterns is presented for horizontal, vertical and inclined pipes. A set of experimental data (7702 points, distributed among 22 authors) and a set of synthetic data generated using OLGA Multiphase Toolkit v.7.3.3 (59 674 points) were gathered. A filtering process based on the experimental void fraction was proposed. Moreover, a classification of the pattern flows based on a supervised classification and a probabilistic flow pattern map is proposed based on a Bayesian… Show more

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Cited by 17 publications
(10 citation statements)
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“…A database consisting of 11,895 data points was compiled considering Amaya et al 's study [9] to validate the results of the analyzed empirical correlations. The data set used is summarized in Table 1.…”
Section: Data Handlingmentioning
confidence: 99%
“…A database consisting of 11,895 data points was compiled considering Amaya et al 's study [9] to validate the results of the analyzed empirical correlations. The data set used is summarized in Table 1.…”
Section: Data Handlingmentioning
confidence: 99%
“…A videography study was carried out during the experiment for each varying condition. Based on the flow classifications proposed by previous researcher [39][40][41][42][43][44][45], the flow patterns observed could be grouped into four main types and subdivided into more detailed classifications as shown in Table 2.…”
Section: Flow Patternmentioning
confidence: 99%
“…Stratified flow or also known as segregated flow is a type of flow where a clear segregation between phases can be seen and that of which produces a definitive interface between them [45]. There are two types of stratified flow, namely stratified smooth and stratified wavy.…”
Section: Stratified Flowmentioning
confidence: 99%
“…Taking into account that flow patterns depend on parameters such as pipe inclination, diameter and length, physical properties of the phases, and superficial velocities (Shippen and Bailey, 2012), many machine learning approaches have been developed in the last years to identify flow patterns (e.g. Xie et al (2004); Al-Naser et al (2016); Amaya-Gómez et al (2019)). These methodologies can achieve high predictive performance (e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Al-Naser et al (2016) used ANN for flow pattern identification with a preprocessing stage using natural logarithmic normalization, to reduce overlapping between flow patterns. Amaya-Gómez et al (2019) proposed a Bayesian supervised algorithm with a novel visualization tool for flow pattern maps. Recently, deep learning has provided good results in predicting flow pattern (e.g.…”
Section: Introductionmentioning
confidence: 99%