Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Doctor of Philosophy

Program

Civil and Environmental Engineering

Supervisor

Nehdi, Moncef L.

Abstract

Groundwater infiltration into underground sewer systems has long been a costly issue for municipalities. With reinforced concrete pipe (RCP) being a primary option for sewer systems, existing hydrostatic testing methods conducted by manufacturers to measure internal pipe pressure, as required by specifications, do not reflect in-situ external hydrostatic conditions. This thesis records the development of a novel testing method to evaluate the RCP joint performance for infiltration. The test is safe and easy to conduct by RCP producers at the factory. The test method mimics field conditions of possible RCP joint gap and joint offset. Over 100 tests were conducted, including 600 mm, 900 mm and 1200 mm RCP with conventional single offset self-lubricated gaskets. This study also evaluates the gasket performance for infiltration. Pipe joint performance curves were developed based on the test results. Comparison to laboratory load deformation tests on gaskets were conducted, indicating that predictions of the sealing potential derived using gasket geometry agreed well with results of infiltration tests. The study shows that the joint gap plays an important role in the sealing potential. The developed apparatus allows the observation of gasket movement under infiltration pressure against the gasket leading to failure. The performance curves also allow the prediction of an infiltration potential leading to a practical applicational procedure to guide RCP installation. A case study of deep RCP pipe subjected to groundwater pressure illustrated the usefulness of the performance curves to derive maximum allowable joint gaps, which contractors could rely on during RCP installation. The findings should allow deducing technical guidance on how water tightness of RCP can be achieved at installation below the prevailing groundwater level. Two oversampling methods: Synthetic Minority Over-sampling Technique (SMOTE) and Density-Based SMOTE were employed to address the unbalanced dataset. Accordingly, applying advanced machine learning techniques, the scale of variation in the test data can be analyzed and accurately predicted using tree-based supervised classification methods: random forest, extra trees and gradient boosting.

Summary for Lay Audience

Groundwater infiltration into sewer systems is a costly problem for many municipalities. With reinforced concrete pipe (RCP) being one of the most commonly used pipe options for sewer systems, existing hydrostatic testing methods conducted by manufacturers measuring internal pressure do not reflect in-situ external hydrostatic conditions. This thesis presents the development of a novel testing method to evaluate the RCP joint performance for infiltration. The test is safe and easy to conduct by RCP producers at the factory. The test also mimics the field conditions of possible joint gaps and joint offsets. The test procedure was repeated many times for 600 mm, 900 mm and 1200 mm RCP. The performance of commonly used single offset self-lubricated gaskets and various alignments were evaluated. Performance curves were developed based on the testing results. Comparisons to the laboratory load deformation tests on gaskets were also conducted indicating that predictions of the sealing potential derived using gasket geometry agreed with results of the infiltration tests. The study shows that the joint gap plays an important role in the sealing potential. The apparatus developed allows the observation of gasket movements under infiltration pressures against the gasket leading to failure. The performance curves also allow the prediction of an infiltration potential leading to a practical applicational procedure to guide the installation of the pipe. A case study of deep RCP pipe subjected to groundwater pressure illustrated the usefulness of the performance curves to derive maximum allowable joint gap, which contractors could rely on during RCP installation. The findings should allow deducing technical guidance on how water tightness of RCP can be achieved at installations below the prevailing groundwater level. Lastly, with the application of advanced machine learning techniques, the scale of the variation in the test data can be analyzed and predicted using classification methods. The modeling technique, procedure and accuracy evaluation are presented.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Appendix A - Design of the Testing Apparatus.pdf (4857 kB)
Appendix A - Design of the Testing Apparatus

Appendix B - Test Results.pdf (14057 kB)
Appendix B - Test Results

Appendix C - Python Source Code.pdf (6179 kB)
Appendix C - Python Source Code

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