Analysis of multiphase flow simulations and comparison with high-speed video observations

Schmelter, Sonja; Olbrich, Marc; Knotek, Stanislav; Bär, Markus

doi:10.1016/j.measen.2021.100154

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…The characterization of slug flow with length and time scales as well as frequency spectra of the complete liquid level time series, obtained from the results of the proposed deep learning based image processing technique have already been used in the investigation of flow experiments and validation of numerical simulations, see Schmelter et al (2021b). Altogether, it can be concluded that the trained model can handle different types of data and provides reliable results for its specific task.…”

Section: Further Evaluations On Different Data Setsmentioning

confidence: 96%

Deep learning based liquid level extraction from video observations of gas–liquid flows

Olbrich

Riazy²,

Kretz³

et al. 2022

International Journal of Multiphase Flow

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Section: Further Evaluations On Different Data Setsmentioning

confidence: 96%

Deep learning based liquid level extraction from video observations of gas–liquid flows

Olbrich

Riazy²,

Kretz³

et al. 2022

International Journal of Multiphase Flow

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“…Since the flow is observed through a relatively thick transparent pipe wall, the liquid level observed from outside is distorted compared to the real liquid level. Hence, a correction based on Snell-Descartes law and trigonometry is applied, see [15] for details. Note that, in the videos, only 94 % of the pipe are visible due to the construction of the Perspex viewing section.…”

Section: Extraction Of Liquid Level Time Seriesmentioning

confidence: 99%

Comparison of different slug frequency calculation methods for the validation of two-phase flow simulations

Schmelter¹,

Knotek²,

Olbrich³

et al. 2023

Proceedings of the 19th International Flow Measurement Conference 2022 on Flow Measurement - FLOMEKO 2022

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Slug flow is a common flow pattern, which is often accompanied by undesired effects, like pressure loss or vibrations, leading to large errors in multiphase flow metering. Because these undesired effects strongly correlate with the frequency of slug occurrence, this parameter is of special interest. In this paper, different slug frequency calculation methods are applied to data from multiphase flow simulations and corresponding high-speed video observations for six test cases within the plug / slug flow regime. Commonly used methods, like power spectral density (PSD) or calculating the mean slug frequency by applying a fixed threshold, are compared with new evaluation methods. Since every approach has its pros and cons, it is recommended to apply different methods to each data set. The deviations in the resulting slug frequencies indicate how much one can trust the results. If large variations are observed, one should apply an advanced technique for the calculation of the liquid level / hold-up, which takes aeration into account.

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“…Therefore, a correction was applied, which is based on Snell-Descartes law and trigonometry. Details on this correction algorithm can be found in our earlier work [39]. The slug flow was recorded for approximately 122 s. Note that, only 94% of the inner diameter of the pipe are visible in the experimental observation, due to the construction of the Perspex viewing section.…”

Section: Extraction Of Liquid Level Time Seriesmentioning

confidence: 99%

On the influence of inlet perturbations on slug dynamics in horizontal multiphase flow—a computational study

et al. 2021

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When multiphase flows are modeled numerically, complex geometrical and operational features of the experiments, such as the phase mixing section, are often not resolved in detail. Rather simplified boundary conditions are prescribed, which usually cause less irregular dynamics in the system than present in reality. In this paper, a perturbation that randomly disturbs the secondary components of the velocity vector at the inlet is proposed in order to capture the experimentally observed instabilities at the interface between the phases. This in particular enhances the formation of slugs in the pipe. Different amplitudes of the perturbation are investigated. One observes that, the higher the perturbation amplitude, the earlier the slugs occur. On the other hand, sufficiently far away from the inlet, the flow pattern shows the same dynamics for different perturbation amplitudes. Hence, no specific frequency is imposed by the prescribed perturbation. The simulation results are validated by comparison with liquid level data from a corresponding experiment.

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Analysis of multiphase flow simulations and comparison with high-speed video observations

Cited by 4 publications

References 7 publications

Deep learning based liquid level extraction from video observations of gas–liquid flows

Deep learning based liquid level extraction from video observations of gas–liquid flows

Comparison of different slug frequency calculation methods for the validation of two-phase flow simulations

On the influence of inlet perturbations on slug dynamics in horizontal multiphase flow—a computational study

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