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Locating leakage in pipelines based on the adjoint equation of inversion modeling

This paper presents an adjoint method for locating potential leakage in a single-phase fluid pipeline based on the analytic solution of inversion modeling. By studying the mechanism of pipeline leakage pressure, the adjoint equation based on the governing equation of transient flow is established in...

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Detalles Bibliográficos
Autores principales: Chang, Chang, Li, Xiangli, Duanmu, Lin, Li, Hongwei, Zhou, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293730/
https://www.ncbi.nlm.nih.gov/pubmed/37383185
http://dx.doi.org/10.1016/j.heliyon.2023.e17270
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author Chang, Chang
Li, Xiangli
Duanmu, Lin
Li, Hongwei
Zhou, Wenbin
author_facet Chang, Chang
Li, Xiangli
Duanmu, Lin
Li, Hongwei
Zhou, Wenbin
author_sort Chang, Chang
collection PubMed
description This paper presents an adjoint method for locating potential leakage in a single-phase fluid pipeline based on the analytic solution of inversion modeling. By studying the mechanism of pipeline leakage pressure, the adjoint equation based on the governing equation of transient flow is established in the single-liquid phase aspect using inverse adjoint theory and sensitivity analysis method. The inverse transient adjoint equation is primarily derived from the single linear fluid pipeline in the semi-infinite domain. The Laplace method is then used to obtain an analytical solution that determines the location of pipeline leakage. The experimental results indicate that the analytic solution can quickly and accurately judge the leakage location of the pipeline. Furthermore, it presents a new approach to engineering applications, such as gas-liquid two-phase flow complex pipe networks, etc.
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spelling pubmed-102937302023-06-28 Locating leakage in pipelines based on the adjoint equation of inversion modeling Chang, Chang Li, Xiangli Duanmu, Lin Li, Hongwei Zhou, Wenbin Heliyon Research Article This paper presents an adjoint method for locating potential leakage in a single-phase fluid pipeline based on the analytic solution of inversion modeling. By studying the mechanism of pipeline leakage pressure, the adjoint equation based on the governing equation of transient flow is established in the single-liquid phase aspect using inverse adjoint theory and sensitivity analysis method. The inverse transient adjoint equation is primarily derived from the single linear fluid pipeline in the semi-infinite domain. The Laplace method is then used to obtain an analytical solution that determines the location of pipeline leakage. The experimental results indicate that the analytic solution can quickly and accurately judge the leakage location of the pipeline. Furthermore, it presents a new approach to engineering applications, such as gas-liquid two-phase flow complex pipe networks, etc. Elsevier 2023-06-14 /pmc/articles/PMC10293730/ /pubmed/37383185 http://dx.doi.org/10.1016/j.heliyon.2023.e17270 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Chang, Chang
Li, Xiangli
Duanmu, Lin
Li, Hongwei
Zhou, Wenbin
Locating leakage in pipelines based on the adjoint equation of inversion modeling
title Locating leakage in pipelines based on the adjoint equation of inversion modeling
title_full Locating leakage in pipelines based on the adjoint equation of inversion modeling
title_fullStr Locating leakage in pipelines based on the adjoint equation of inversion modeling
title_full_unstemmed Locating leakage in pipelines based on the adjoint equation of inversion modeling
title_short Locating leakage in pipelines based on the adjoint equation of inversion modeling
title_sort locating leakage in pipelines based on the adjoint equation of inversion modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293730/
https://www.ncbi.nlm.nih.gov/pubmed/37383185
http://dx.doi.org/10.1016/j.heliyon.2023.e17270
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