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Probability Prediction Model of the Maximum Corrosion Depth of Concrete Sewage Pipes.

Authors :
Gao, Xiangling
Wang, Lina
Liu, Wei
Source :
Journal of Pipeline Systems Engineering & Practice. Nov2023, Vol. 14 Issue 4, p1-14. 14p.
Publication Year :
2023

Abstract

Concrete pipes are used widely in sewage pipeline networks due to their superior stiffness, bearing capacity, and low price. However, as the service age increases, the microorganisms inside the pipeline react with the concrete pipe walls and induce concrete pipe wall corrosion. Microbiologically induced corrosion (MIC) is serious corrosion in concrete sewage pipe walls, resulting in a reduction of the wall's thickness and causing the cover soil above the buried pipeline to collapse. The real-time corrosion in concrete sewage pipe walls was simulated in this study. A numerical simulation of the MIC in concrete sewage pipes was performed using the software COMSOL Multiphysics, in which the randomness of the MIC was considered by introducing the random distribution of concrete porosity and corrosive substance concentration; the influence of the turbulence and the transfer rate of H2S were considered by zoning the section of the pipe wall. Combined with the probability density evolution theory, a probability model is proposed to predict the maximum corrosion depth of the concrete sewage pipe wall. The results show that the maximum corrosion depth in the pipeline is more likely to occur in the vicinity of the sewage level and the pipe crown, and its dispersion increases with time and decreases as corrosive substance concentration increases. After verification, the model presented can be used to predict the time-dependent reliability and the service life of concrete sewage pipes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19491190
Volume :
14
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Pipeline Systems Engineering & Practice
Publication Type :
Academic Journal
Accession number :
172023050
Full Text :
https://doi.org/10.1061/JPSEA2.PSENG-1198