Graduation Year

2023

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Qing Lu, Ph.D.

Committee Member

Qiong Zhang, Ph.D.

Committee Member

Mingyang Li, Ph.D.

Committee Member

Xiaopeng Li, Ph.D.

Committee Member

Steven Reader, Ph.D.

Keywords

Co-location Interdependency, Truck Impact, Interdependency Cases, Interdependency Impact, Spatial Interdependency

Abstract

This dissertation studies the interdependency between road and water infrastructures and associated interdependency impact on these two critical infrastructure systems. Critical infrastructures and the interdependency among these infrastructures have gained much attention recently because of its growing complexity, importance, and vulnerability to natural and man-made threats. In response, researchers have spent significant effort to study these infrastructures individually as well as when they are interdependent to understand complex interdependency relationship and to figure out ways to make these infrastructures more reliable, robust, and resilient. However, water and road infrastructure systems have not been studied as vastly as other critical infrastructures despite the former two being very important systems providing essential services to the community. To address the issue, this dissertation strives to answer fundamental questions in relation to the interdependency between water and road infrastructures. It also studies the expected interdependency impact on every part of these two infrastructure networks.

Interdependency relationship may occur in more than one way in any two interdependent infrastructure systems. These mechanisms are referred to as interdependency cases or events. Understanding these interdependency cases is a quite fundamental aspect of studying interdependency. Interdependency cases related to water and road infrastructures have not been outlined in the literature. This dissertation conducts a systematic review of news articles, literature and case studies to find events that have significant impact on both of these infrastructures to the extent that it would get attention from news media and/or researchers. A nationwide survey was also conducted among personnel working in the infrastructure agencies to learn about incidents affecting both infrastructures. The findings from this effort resulted in a list of interdependency events that impact both water and road infrastructures and are worth further investigation. One particular interdependency case, which is the impact of heavy truck movement along road infrastructure on underlying water pipes, was important in deciding whether the interdependency between water and road infrastructures is bi-directional or unidirectional in nature. If heavy vehicles have significant impact on pipe breaks, it will mean that both road and water pipe infrastructures affect each other. Whereas there are many cases in which water infrastructure affects road infrastructure it would be the only case where the reverse event occurs. To study this particular case, this dissertation constructed a structural model of buried pipe subjected to maximum possible vehicle load allowed by Federal Highway Administration (FHWA) regulations. The model also simulated extreme conditions such as aged and corroded pipe, sinkhole under the pipe to investigate if the vehicle load contributes to pipe break when the pipe is far from ideal conditions. The result indicates that the vehicle load alone does not cause pipe break rather in all the loading scenarios the pipe deflection was within serviceable limits set by American Water Works Association (AWWA).

Finally, this dissertation proposed a framework to study the interdependency impact caused by one very common interdependency case: road network gets affected when water pipe breaks. The proposed framework is comprehensive because it also takes the risk and vulnerability of the infrastructures into consideration. This framework is implemented in a case study by applying its methodologies in the interdependent road and pipe networks in the City of Tampa, Florida. The framework calculated three different metrics in three modules which capture risk, co-location interdependency and consequence of failure propagation to the road network. In the final step, these metrics were combined to estimate a final interdependency impact metric. Specific methodologies were implemented to estimate the metrics associated to three modules in the case study, although other relevant methods can be resorted to while applying the metric in other interdependent networks in other places depending on available data and systems in place. In the case study a decision tree model was developed based on aggregated historic pipe failure data of the study network. Failure likelihood estimated by this model gave the risk estimation metric. A spatial analysis was conducted to quantify the degree of co-location between water and road networks which captured the failure propagation likelihood in the second module of the framework. In the third module, roadway link closure was simulated using regional travel demand model as implemented in the Tampa Bay Regional Planning Model (TBRPM) V8.0 for the Tampa Bay region. Results from this module captured the consequence of failure propagation from the water network to the road network. In the final step, the metrics from all three modules were combined to estimate expected interdependency impact in all parts of the network of both infrastructures. When presented in a network map, the final metric represents infrastructure condition, risk and vulnerability from the perspective of interdependency between the two infrastructure networks. Results from this framework implementation can help water and road infrastructure agencies to account for interdependency impact in resource allocation during maintenance and rehabilitation effort and can also help in preparing for worse consequences associated with interdependency failure propagation and its impact.

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