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Toward a high-fidelity model for the identification of underground gas flow regimes resulting from buried pipeline releases

journal contribution
submitted on 2023-11-08, 09:36 and posted on 2023-11-08, 10:48 authored by Ola Srour, Konstantinos E. Kakosimos, Luc N. Vechot

The quantitative characterization of underground transport phenomena remains challenging due to the complex behavior of the gas movement in soil. Conversely, this inhibits the accurate prediction of the risk arising from the underground transport of hazardous materials. This work proposed and qualitatively evaluated a computational model that spans a wide range of underground gas flow regimes, ranging from gas migration, to ground uplift, and crater formation, depending on the release characteristics. The model followed the multiphase Eulerian approach and adopted the standard k-ω turbulence model and the kinetic theory of granular flow for the ground description with the Syamlal-O’Brien granular viscosity expression. The model's optimum configuration was checked against experimental data using a new mechanistic approach to link the qualitative observations with quantitative model outputs. The effect of pipeline pressure, burial depth, and release orientation on the regime was studied and the outcomes were utilized to enhance a literature nomograph for the flow regime identification. Emphasis was given to fill in the literature gaps and improve the delineation of the boundaries between the regimes rather than deriving specific quantities. The resulted nomograph is a cost-effective screening tool to identify the regime and select among the available strategies of risk assessment.

Other Information

Published in: Journal of Natural Gas Science and Engineering
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.jngse.2022.104832

Funding

Open Access funding provided by the Qatar National Library

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Texas A&M University at Qatar
  • Mary Kay O'Connor Process Safety Center - TAMUQ

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