Technical Papers
Mar 25, 2022

Effects of Network Uncertainty on Seismic Vulnerability Assessment of Water Pipe Networks

Publication: Journal of Pipeline Systems Engineering and Practice
Volume 13, Issue 3

Abstract

Past earthquakes have revealed that earthquakes disrupt operations of underground water infrastructure systems. Assessment of the seismic vulnerability of underground water pipe networks plays a critical role in formulating preventive rehabilitation decision making to avoid high repair costs. Although existing seismic vulnerability assessment methods are sensitive to water pipe network uncertainties (e.g., uncertainties in nodal demand, reservoir head, and pipe roughness coefficient), the extent of the effects of these uncertainties on the postearthquake serviceability of the networks has not been examined. This research investigates the effects of water pipe network uncertainties on the seismic vulnerability assessment of networks. Transient ground displacements due to seismic wave propagation are considered for this investigation. The methodology includes seven steps: uncertainty identification and quantification, design of experiments, integrated multiphysics modeling, seismic repair rate calculations, Monte Carlo simulation, statistical analysis of the data (ANOVA and Tukey tests), and sensitivity analysis. Uncertainties in nodal demand, reservoir head, and pipe roughness coefficient were examined in this study. An integrated multiphysics model was created to simulate hydraulic network behavior and seismic vulnerability assessment. The approach was tested on two networks (New York Tunnel Network and Oberlin Network). The statistical analysis results indicated that the combined impact of the three selected water pipe network uncertainties on the seismic vulnerability assessment of networks is statistically significant. Nodal demand and pipe roughness coefficient uncertainties did not individually have a statistically significant effect. The individual effect of reservoir head uncertainty was statistically significant. Sensitivity analysis determined the minimum value of the coefficient of variation to have a statistically significant effect. Sensitivity analysis was divided into three parts to investigate the individual and combined effects of network uncertainties. The results from sensitivity analysis showed that a small uncertainty in reservoir head results in a statistically significant effect on seismic vulnerability assessment. By contrast, the coefficient of variation for uncertainties in nodal demand and pipe roughness has to be quite large to significantly affect seismic vulnerability assessment. Statistical analysis and sensitivity analysis results showed that water pipe network uncertainties have a statistically significant impact on seismic vulnerability assessment of networks. Hence, it is recommended to integrate water pipe network uncertainties with existing methods for assessing seismic vulnerabilities.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This material is based upon work supported by the National Science Foundation under Grant CMMI-1926792. Hence, the authors are grateful to the National Science Foundation for this support.

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Go to Journal of Pipeline Systems Engineering and Practice
Journal of Pipeline Systems Engineering and Practice
Volume 13Issue 3August 2022

History

Received: May 9, 2021
Accepted: Feb 7, 2022
Published online: Mar 25, 2022
Published in print: Aug 1, 2022
Discussion open until: Aug 25, 2022

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Abhijit Roy, S.M.ASCE [email protected]
Graduate Student, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S. Yates St., Arlington, TX 76019. Email: [email protected]
Mohsen Shahandashti, M.ASCE [email protected]
Associate Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S. Yates St., Arlington, TX 76019 (corresponding author). Email: [email protected]
Professor, Dept. of Industrial, Manufacturing, and Systems Engineering, Univ. of Texas at Arlington, 416 S.Yates St., Arlington, TX 76019. ORCID: https://orcid.org/0000-0003-4038-1402. Email: [email protected]

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