Journal Published Online: 28 July 2022
Volume 50, Issue 5

The Testing Methods and Prediction Models for Concrete Corrosion in Sewer Pipelines: A State-of-the-Art Review

CODEN: JTEVAB

Abstract

Microbiologically induced concrete corrosion (MICC) is a specific occurrence in sewer systems where the cementitious materials are eroded toward a paste by microbiological processes. MICC has been one of the factors causing huge asset losses and urban hazards worldwide. Addressing this issue, some tests investigating the long-term performance of sewer pipes have been carried out, and a good number of testing data has been accumulated since the end of the 19th century. In this paper, these experimental works and results are collected in the expectation that they serve as a basis for service life prediction. Therefore, long-term performance test methods for sewage pipes including sulfuric acid (H2SO4) acid immersion, microbial feeding chambers, demonstration plants, in situ tests, artificially enhanced effluent erosion, and artificial pipe wall thinning are comprehensively reviewed. Meanwhile, the applicability of each method is discussed regarding its merits. Furthermore, the proposed data-driven corrosion models are outlined, and it is found that the input data for these models are primarily testing results because of the incomplete and lack of historical operational data sets. Future efforts aimed at the remaining life prediction for sewer pipelines are also suggested. The present work will serve as a guide and offer new insights for those who are preparing to investigate the long-term performance of sewer pipes.

Author Information

Wang, Yajian
National Center for Materials Service Safety, University of Science and Technology Beijing (USTB), Beijing, China
Li, Pengpeng
National Center for Materials Service Safety, University of Science and Technology Beijing (USTB), Beijing, China
Wang, Linbing
Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
Pages: 25
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE20210702
ISSN: 0090-3973
DOI: 10.1520/JTE20210702