Peer-reviewed veterinary case report
How to detect leaks in underwater gas-liquid pipelines with plug flow
By Ferroudji H et al.·2026·Hydrocarbons and Chemistry Faculty·View original on Europe PMC →
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Original publication title: Analysis and nomograph development for a leaky pipeline carrying plug flow based on numerical modeling and experimental validation.
Plain-English summary
This study looks at how to detect leaks in pipelines that carry a mix of gas and liquid, which can be tricky because the flow can change rapidly. Traditional methods for finding leaks work better with single types of fluids and often give false alarms when used with mixed flows. The researchers created a computer model to simulate different leak scenarios and tested it against real-life experiments. They found that leaks change the pressure and gas distribution in the pipeline, and the ability to detect these leaks depends on the flow conditions and the size of the leak. Their new tool for estimating how fast gas escapes from underwater leaks showed good results compared to the experiments, suggesting it could be useful for safety checks in these types of pipelines.
Abstract
Leak detection in pipelines transporting gas-liquid multiphase flow remains a challenging task due to complex and inherently unsteady flow behavior, particularly under intermittent regimes such as plug flow. Conventional leak detection techniques, which are well established for single-phase flow, often suffer from reduced sensitivity and false alarms when applied to multiphase systems. Motivated by these limitations, the present study investigates leakage characteristics in a horizontal pipeline conveying gas-liquid plug flow under underwater conditions. A three-dimensional transient numerical model based on the Volume of Fluid (VOF) approach is developed to simulate various leakage scenarios, including different discharge sizes and gas-liquid superficial velocities. The numerical results are validated against experimental data obtained from a dedicated multiphase flow loop. Time-series pressure signals are analyzed using statistical metrics, probability density functions, and continuous wavelet transform techniques to assess their effectiveness in identifying leakage occurrence. Furthermore, a non-dimensional analysis is employed to develop a nomograph for estimating gas release velocity from underwater leaks. The results demonstrate that leakage significantly alters pressure fluctuation characteristics and gas void fraction distribution, with detectability strongly influenced by flow conditions and discharge size. The proposed nomograph predicts gas release velocity with reasonable agreement relative to experimental measurements, highlighting its potential applicability for subsea leak assessment and process safety analysis in multiphase pipeline systems.
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Search related cases →Original publication on Europe PMC: https://europepmc.org/article/MED/41781428