Date of Award


Document Type

Thesis - Open Access

Degree Name

Master of Science in Transportation Engineering


Civil Engineering

Committee Chair

Scott A. Parr, Ph.D.

First Committee Member

Christopher D. Grant, Ph.D.

Second Committee Member

Hongyun Chen Ph.D.


The National Science Foundation’s definition of resiliency is “the ability to prepare and plan for, absorb, recover from, or more successfully adapt to actual or potential adverse events” (National Science Foundation, 2016). While this definition is informative and useful, it lacks a quantitative reference. There is a need for a method of quantifying resilience to better plan and prepare for system wide disruptions. The research effort described herein provides a quantifiable measures of system resiliency, consistent with NSF’s definition. Fundamentally, a system disruption can be partitioned into five distinctive states: the stable pre-event state, the absorption state, the disrupted state, the recovered state, and stable recovered state. The proposed method identifies these states by measuring system output and quantifies each component on a value scale between zero and one. The resiliency measure then unifies these metrics to provide an overall assessment of resiliency, which accounts for the system’s ability to absorb, recover, and adapt. This approach to quantifying resiliency is applicable to any real-world or simulated system with measureable outputs. This paper first documents the development of the resiliency quantification method and then applies the method toward four complex, real world, transportation systems undergoing disruptions. These case studies consisted of six maritime port, three airports, two localized refueling systems, and the Colorado Department of Transportation’s cyber network. Each system had a measurable drop in functionality due to a disruption. In general the results of this research showed that the proposed method of quantifying resiliency can be utilized for any transportation system.