Defect-Based Condition Assessment Model for Sewer Pipelines Using Fuzzy Hierarchical Evidential Reasoning
Publication: Journal of Performance of Constructed Facilities
Volume 35, Issue 1
Abstract
Assessing the condition of sewer pipelines is essential for addressing associated problems as a result of deterioration to maintain functionality and avoid additional social costs. This paper presents the development of a defect-based condition assessment model for sewer pipelines. The model aims to cover the structural, operational, and rehabilitation defects that are associated with the pipeline, joints, and maintenance holes on pipe segments. The analytic network process (ANP), which considers the interdependencies between pipeline components and defect types, was used to deduce the relative importance weights through questionnaires and interviews with infrastructure experts and professionals. The model employs the defects’ severities to develop fuzzy membership functions based on a predefined linguistic condition grading scale that would precisely indicate the degree of distress. Hierarchical evidential reasoning (HER) and the Dempster-Shafer (D-S) theory were used to integrate the defects’ conditions and to evaluate the overall condition of sewer pipelines, which is represented as a crisp value calculated by the weighted average defuzzification method. A validation dataset was used in the model validation and protocol verification. This model is expected to minimize the inaccuracy of sewer condition assessment through the application of severity, uncertainty mitigation, and robust aggregation. It could also benefit asset managers by providing a precise condition overview for maintenance, rehabilitation, and budget allocation purposes.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider indicated in the “Acknowledgments.”
Acknowledgments
This publication was made possible by National Priorities Research Program (NPRP) Grant No. NPRP6-357-2-150 from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made here in this study are solely the responsibility of the authors. Also, the authors would like to thank the public works authority of Qatar (ASHGAL) for their support in the data collection.
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Journal of Performance of Constructed Facilities
Volume 35 • Issue 1 • February 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 25, 2020
Accepted: Sep 14, 2020
Published online: Dec 7, 2020
Published in print: Feb 1, 2021
Discussion open until: May 7, 2021
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