Thorat, U. orcid.org/0000-0001-6563-4520, Jones, M., Woollam, R. orcid.org/0000-0002-5394-5281 et al. (4 more authors) (2024) Computational fluid dynamics driven mass transfer model for the prediction of CO2 corrosion in pipelines. Journal of Pipeline Science and Engineering, 4 (1). 100148. ISSN 2667-1433
Abstract
A novel, computational fluid dynamics (CFD) driven modelling methodology for predicting CO2 corrosion rates in pipelines is presented. CFD is used to provide accurate predictions of the viscous sublayer thickness and turbulent diffusivities, which are then used within a mass transfer model of aqueous CO2 corrosion. Comparisons with experimental measurements of corrosion rate in horizontal pipe flow and corresponding theoretical predictions, based on empirical correlations and previous CFD approaches, show the new approach is more accurate for flows in the range of pH 4 to 6. However, the key advantage of the new approach is its flexibility. Existing models are inaccurate and highly restrictive, having been derived for very simple cases, such as 1 D pipe flow. In contrast, the new methodology provides a firm, scientific foundation for predicting corrosion rates by determining conditions in the viscous sublayer in much more complex, and practically relevant, flow situations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | CO2 corrosion; Mass transfer model; Pipeline flow; Numerical modelling; Computational fluid dynamics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Functional Surfaces (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Jun 2024 14:56 |
Last Modified: | 20 Jun 2024 14:56 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jpse.2023.100148 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:213696 |