ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Civil Engineering


Civil Engineering

First Advisor

Mohammad Najafi


This dissertation presents the viability of managing a pipeline network adjacent to bodies of water to maximize asset life by evaluating the significant factors that affect the condition levels of pipeline assets. Pipeline asset management derives from pipelines’ physical conditions, condition rating, and serviceability through testing, monitoring, and analyzing rupture history. The remaining asset life and structural condition of the pipeline network running near and under bodies of water are often hard to predict. In case of pipeline failure, exuberant damages will occur to the surrounding environment, adding up to disruption in service and repairing costs. This research develops Multinomial Logistic Regression (MLR) and Binary Logistic Regression models to predict how the bodies of water could affect the soil surrounding wastewater interceptors. The models were developed based on data from the City of Fort Worth, Texas. This dissertation concludes that pipe diameter, pipe age, location of the pipeline with reference to bodies of water, either far or near, and the pipe material (HDPE, CI, DI, PVC, and Concrete) are the most significant variables that effect the surrounding soil conditions for wastewater interceptors. As we gain a clearer perception through increased software development for managing pipeline data, system programming using statically programming (such as Golang) could be conducted in the future.


Asset management, Wastewater interceptors, Wastewater pipelines, Bodies of water, Rivers, Lakes, Surrounding conditions, Surrounding soil


Civil and Environmental Engineering | Civil Engineering | Engineering


Degree granted by The University of Texas at Arlington