Currently, water utilities are facing monetary crises to maintain and expand services to meet the current as well as the future demands. Standard practice in pipeline infrastructure asset management is to collect data and predict the condition of pipelines using models and tools. Water utilities want to be proactive in fixing or replacing the pipes as fixing-when-it-fails ideology leads to increased cost and can affect environmental quality and societal health.
There is a number of modeling techniques available for assessing the condition of the pipelines, but there is a massive shortage of methods to check the reliability of the results obtained using different modeling techniques. It is mainly because of the limited data one utility collects and absence of piloting of these models at various water utilities.
In general, water utilities feel confident about their in-house condition prediction and failure models but are willing to utilize a reliable methodology which can overcome the issues related to the validation of the results. This paper presents the methodology that can enhance the reliability of model results for water pipeline performance analysis which can be used to parallel the output of the real system with confidence. The proposed methodology was checked using the dataset of two large water utilities and was found that it can potentially help water utilities gain confidence in their analyses results by statistically signifying the results. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/84401 |
| Date | 25 July 2018 |
| Creators | Patel, Pruthvi Shaileshkumar |
| Contributors | Civil and Environmental Engineering, Sinha, Sunil Kumar, Sears, Lee, Leon, Roberto T. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0016 seconds