Development of Comprehensive Rating for the Evaluation of Sewer Pipelines

• Published in: Journal of pipeline systems 2023-05, Vol.14 (2)
• Main Authors: Betgeri, Sai Nethra, Matthews, John C., Vladeanu, Greta
• Format: Article
• Language: English
• Subjects: Analytic hierarchy process; Closed circuit television; Corrosion; Decision analysis; Decision making; Defects; Evaluation; History; Human error; Pipes; Preventive maintenance; Seismic zones; Sewer maintenance; Sewer pipes; Sewer systems; Soil conditions; Soils; Spatial data; Technical Papers; Television; Visual inspection; Visual observation; Wastewater
• ISSN: 1949-1190; 1949-1204
• DOI: 10.1061/JPSEA2.PSENG-1208

AbstractThe Pipeline Assessment and Certification Program (PACP) was developed by the National Association of Sewer Service Companies, the industry-accepted protocol for condition rating sewer pipes in the US. The PACP method relies exclusively on visual inspections performed using closed-circuit television (CCTV), where certified operators observe existing structural and operation and maintenance (O&M) defects limitation of the PACP method is that it does not use pipe characteristics, depth, soil type, surface conditions, pipe criticality, and capacity, nor the distribution of structural defects or history of preventative maintenance to determine the condition rating of the sewer pipe segment. Therefore, this research addresses the limitations of the PACP with the development of a new wastewater pipe rating system known as the comprehensive rating (CR) system. The CR evaluation system is based on a commonly used decision-making approach known as the analytical hierarchy process (AHP) to analyze problems and issues. The new CR model incorporates pipe characteristics (age, corrosion, diameter, and shape), external characteristics (depth, soil type, traffic loading, waste type, seismic zone), and hydraulic characteristics (structural score, O&M score, and repair history). The results showed a below-average validity percentage because linear regression assumes a linear relationship between the input and output variables but the relationship between the response and the predictor is not linear.The CR methodology can be improved by increasing the number and variability of experts who evaluate the condition of existing sewer pipes, enhancing geospatial data for locational accuracy, and establishing evaluation standards for inspectors to minimize human error. More research is needed to determine a suitable nonlinear relation that can be used to model data from this new comprehensive rating system.