Improving the estimation of slug frequency from two-phase flow simulations in horizontal pipelines

Abstract Slug flow is a common flow pattern that is often accompanied by undesired effects, such as important pressure loss or vibrations, leading to large errors in multiphase flow metering. As these undesirable effects strongly correlate with the frequency of slug occurrence, this parameter is of particular interest. In this paper, different methods for calculating the slug frequency are applied to data from multiphase flow simulations and corresponding high-speed video observations. Commonly used methods, such as power spectral density or calculating the mean slug frequency by counting slugs, are compared with new evaluation methods proposed by the authors. These new methods are based on the distribution of the time difference between consecutive slugs. Since these methods place more weight on frequencies that occur more often, they are less sensitive to outliers in the slug frequency distribution. For the developed slug flow, good agreement is observed between the different slug frequency calculation methods and between the experimental data and simulation results. In contrast, significant differences between simulations and experiments can occur when the flow pattern is still developing. In this case, the deviations in the resulting slug frequencies when different calculation methods are applied can indicate how much one can trust the results. Comparing the results derived by the different methods with reference values, which were obtained by visually counting the slugs in the videos, shows the best agreement for the newly introduced peak slug frequency, with a relative error of less than 10% on average and circa 24% maximum.

Authors

Publication Details

Journal
Experimental and Computational Multiphase Flow
Published
2026-04-20
DOI
https://doi.org/10.1007/s42757-025-0268-8
Primary Topic
Fluid Dynamics and Mixing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving the estimation of slug frequency from two-phase flow simulations in horizontal pipelines

Stanislav Knotek, Sonja Schmelter, Marc Olbrich, Markus Bär
Experimental and Computational Multiphase Flow
Fluid Dynamics and Mixing
article

Improving the estimation of slug frequency from two-phase flow simulations in horizontal pipelines

Stanislav Knotek, Sonja Schmelter, Marc Olbrich, Markus Bär
article en

Abstract

Abstract Slug flow is a common flow pattern that is often accompanied by undesired effects, such as important pressure loss or vibrations, leading to large errors in multiphase flow metering. As these undesirable effects strongly correlate with the frequency of slug occurrence, this parameter is of particular interest. In this paper, different methods for calculating the slug frequency are applied to data from multiphase flow simulations and corresponding high-speed video observations. Commonly used methods, such as power spectral density or calculating the mean slug frequency by counting slugs, are compared with new evaluation methods proposed by the authors. These new methods are based on the distribution of the time difference between consecutive slugs. Since these methods place more weight on frequencies that occur more often, they are less sensitive to outliers in the slug frequency distribution. For the developed slug flow, good agreement is observed between the different slug frequency calculation methods and between the experimental data and simulation results. In contrast, significant differences between simulations and experiments can occur when the flow pattern is still developing. In this case, the deviations in the resulting slug frequencies when different calculation methods are applied can indicate how much one can trust the results. Comparing the results derived by the different methods with reference values, which were obtained by visually counting the slugs in the videos, shows the best agreement for the newly introduced peak slug frequency, with a relative error of less than 10% on average and circa 24% maximum.

Experimental and Computational Multiphase Flow
Openalex Percentile: Top 8%
Fluid Dynamics and Mixing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.