ORCID Identifier(s)

0000-0001-8101-1964

Graduation Semester and Year

2021

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Civil Engineering

Department

Civil Engineering

First Advisor

Sharareh Dr. Kermanshachi

Abstract

Local as well as national economy and safety depend on the network characteristics of the transportation infrastructures. Destruction of transportation infrastructures causes the direct cost of the reconstruction as well as indirect cost due to loss of mobility. In addition, emergency response and recovery cannot be rendered if access to the affected community is hampered due to a damaged transportation network. Hence, researchers as well national and international organizations are focusing more on a resilience-based approach instead of a traditional recovery-based approach for the transportation infrastructures recently. As a result, there exist a high number of research articles that developed resilience measurement dimensions and models for such infrastructures. Being a relatively new topic in the field of transportation, a comprehensive model to measure the resilience of transportation infrastructure is yet to be developed. Moreover, developed dimensions are incoherent in meaning throughout the literature. Hence, there are a lot of opportunities to enhance the current literature of resilience analysis in transportation infrastructure by integrating different perspectives which are rarely studied. Such a perspective is addressing transportation resilience from the construction and management point of view. Moreover, characteristics of investment and funding which might have an impact on the level of resilience are also a rarely studied topic in transportation network resilience analysis. Therefore, this study aims to establish a list of transportation infrastructure resilience measurement dimensions. This study will also establish a decision-making tool to measure the resilience of the transportation infrastructures as well as determine the relationship of the dimensions with the rapidity of the infrastructures. To fulfill the aim of this study, a questionnaire `was developed based on a comprehensive literature review. Experts in transportation construction and reconstruction projects were chosen as the potential participants for this study and the survey was sent through electronic media. After a couple of reminder emails, 92 valid responses were collected. Collected data were analyzed qualitatively and quantitatively. Statistically significant variables were determined from a total of 35 variables. It was found that there were 21 significant variables based on the criteria involvement in the reconstruction projects. The effect size of each of the 21 variables was determined and based on the effect size they were ranked and scored. It was found that having dedicated investment for future resilience enhancement activities while planning and investing for a new project is the most impactful on the level of resilience of the transportation infrastructure. The variable with the second most effect was the availability of previous disaster data of the roadway. The developed decision-making tool will provide a comparative value for the level of resilience for transportation infrastructures projects. In addition, to understand the impact of significant variables on the rapidity of the project, a model was developed. A sophisticated modeling technique, structural equation modeling (SEM), was used to develop the model to study the causal relationships of the variables with rapidity. Before performing modeling, exploratory factor analysis (EFA) was performed to group the variables into different components. Based on the literature, the hypothesis was made and introduced into the model in the SPSS AMOS. The model was analyzed, and the results are interpreted. It was found that, construct integrated assets has the maximum impact on the rapidity of the transportation infrastructures. Having a railroad crossing integrated on the roadway will have higher possibility to retard the restoration activity of the transportation network by delaying the restoration of other integrated infrastructures. The findings of this study will help decision-makers in prioritizing the projects based on their criticality in resilience level and support their decisions in investing and funding in the most critical transportation infrastructure projects. This study will also help in recognizing critical paths that contribute most to prolonging recovery time and slowing down the recovery speed of a transportation network after a roadway. It will also help practitioners in establishing proper strategies against the corresponding contributing delay factor to improve the resilience of the network.

Keywords

Transportation infrastructure resilience, Resilience measuring dimensions, Critical transportation infrastructure, natural disasters, Resilience, Transportation engineering, Reconstruction, Decision-making tool, Structural equation modeling (SEM) technique

Disciplines

Civil and Environmental Engineering | Civil Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

30701-2.zip (4278 kB)

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