Experimental investigation of sudden expansion's influence on the hydrodynamic behavior of different sub-regimes of intermittent flow

Arabi, Abderraouf; Salhi, Yacine; Zenati, Youcef; Si‐Ahmed, El‐Khider; Legrand, Jack

doi:10.1016/j.petrol.2021.108834

Cited by 14 publications

(9 citation statements)

References 113 publications

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“…13.a, that an increase in the gas super cial velocity induces an increase in the standard deviation, regardless the liquid super cial velocity. This last observation was reported by Luo et al (2010) in a straight pipe and by Arabi et al (2018Arabi et al ( , 2021d at the upstream of a sudden expansion. One should note that as the liquid super cial velocity increases, the gradient of the variation of the standard deviation as a function of V SG increases.…”

Section: Statistical Parameterssupporting

confidence: 56%

“…Our group has obtained interesting results using this classi cation approach in series of recent works. Indeed, it was found that the slug frequency (Arabi et al, 2020), the pressure drop (Arabi et al, 2021c) and the behaviour of the ow structures crossing a sudden expansion (Arabi et al, 2021d), depend on the nature of the sub-regime. Despite these results, the investigations carried out using these sub-regimes classi cation are still scarce, as indicated by the limited number of existing ow pattern maps, showing the zones of the existence of these sub-regimes (Thaker and Banerjee, 2016;Dinaryanto et al, 2018;Humami et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Identifying the intermittent flow sub-regimes using pressure drop time series fluctuations

Arabi

Salhi

Zenati

et al. 2023

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From a literature survey, it has been noticed a lack of objective methods to identify and distinct between the intermittent flow sub-regimes. Thus, the aim of this study is to analyze pressure drop fluctuations using statistical methods in order to propose simple tools to characterize the sub-regimes of the intermittent flow. The pressure drop time series were collected from experiments carried out using air-water mixture and 30 mm ID pipe. The utilization of transparent pipes allowed to identify three sub-regimes which are Plug flow, Less Aerated Slug flow (LAS flow), and Highly Aerated Slug flow (HAS flow). It was found that the PDF displayed a unimodal distribution in all cases studied. Meanwhile, the representation of the base width and maximum values of PDF as function of the gas-to-liquid superficial velocities ratio and the mixture Froude number, respectively, showed that the points for each sub-regime are clustered in the same zone. So, these two feature spaces can be used to identify the sub-regimes. A third feature space, based on the statistical parameters standard deviation and kurtosis, was also proposed as a tool to distinguish between the three sub-regimes.

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Section: Statistical Parameterssupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Identifying the intermittent flow sub-regimes using pressure drop time series fluctuations

Arabi

Salhi

Zenati

et al. 2023

Preprint

Self Cite

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“…Using this approach, some scholars reported that knowing the nature of the ow sub-regimes would help to better correlating the slug frequency (Arabi et al, 2020) and the frictional pressure drop (Arabi et al, 2021c). The interaction of the intermittent ow with the pipes (one of the major challenges of the intermittent ow as explained in the recent review paper about slug ow presented by Mohmmed et al (2021) can be better understood by considering the sub-regimes (Arabi et al, 2021d)). These ndings highlight the importance of using this sub-regime classi cation for a better knowledge of the intermittent ow (Arabi et al, 2024b).…”

Section: (2022)mentioning

confidence: 99%

Analysis of Horizontal Gas-liquid Intermittent Flow Sub-Regimes Transitions: Physical Mechanisms and Flow Maps

Arabi,

salhi,

Zenati

et al. 2023

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These recent years, several experimental investigations were carried out on horizontal gas-liquid two-phase flow by considering the sub-regimes which are plug, Less Aerated Slug (LAS) and Highly Aerated Slug (HAS) flows. These sub-regimes classification is based on the shape of the elongated bubble/liquid slug interface as well as the aeration within liquid slugs. In this work, an extensive experimental visualization was performed using air-water mixture in a 30 mm ID horizontal pipe. The study has covered a total of 189 operating conditions. It was reported, for the first time, that each sub-regime had a specific mechanism for aeration of the liquid slug flow. the presence of gas bubbles within liquid slugs, in the case of plug flow, is due to the interfacial shear induced waves mechanism. The transitions to LAS and HAS flows are accompanied by the appearance of the shearing-off and scooping of the bubbles present in the liquid film into liquid slug mechanisms, respectively. In addition, the reported flow transition lines, as well those existing in the literature, were analyzed using different existing coordinate systems. This analysis allowed finding that the X-T system is the most suitable one for predicting the three flow sub-regimes.

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“…For example, the bubbly ow was investigated by Aloui et al (1996aAloui et al ( , 1996b, Lobanov and Pakhomov (2017), Lobanov et al (2019), Kim and Park (2019), Celis et al (2021) and Bogatko et al (2021). On the other hand, Arabi et al (2018Arabi et al ( , 2021b and Zhang and Goharzadeh (2019) dealt with the intermittent ow. However, as mentioned by Arabi et al (2021b), most studies was focused on the estimation of the pressure change caused by the passage of the gas-liquid two-phase ow through this tting.…”

Section: Introductionmentioning

confidence: 99%

Pressure recovery model for gas-liquid two-phase flow across sudden expansions

Arabi

Abdul-Majeed

Boukrouche

et al. 2023

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The presence of a sudden expansion generates a variation of the static pressure commonly called Pressure Recovery (PR). In this paper, we made firstly an extensive literature survey to list existing gas-liquid two-phase flow pressure recovery models and to collect an experimental database. Thus, a total of 305 data was collected from 6 recent works and 18 predictive models was identified. An analysis of the different existing models was carried out firstly. Then, the predictive capability of nine existing models was assessed using the collected database. It was reported that none of the models can predict the experimental results for a large range of experimental conditions. This finding highlighted the necessity to propose a new model. The proposed predictive model was developed using the two-phase multiplier and mass quality. These two parameters were correlated using 157 data points from the collected database, while the other data was used to validate it. It was found that the proposed model gives better predictions compared to existing ones in the range of conditions and parameters of the experimental database used in this analysis.

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Experimental investigation of sudden expansion's influence on the hydrodynamic behavior of different sub-regimes of intermittent flow

Cited by 14 publications

References 113 publications

Identifying the intermittent flow sub-regimes using pressure drop time series fluctuations

Identifying the intermittent flow sub-regimes using pressure drop time series fluctuations

Analysis of Horizontal Gas-liquid Intermittent Flow Sub-Regimes Transitions: Physical Mechanisms and Flow Maps

Pressure recovery model for gas-liquid two-phase flow across sudden expansions

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