Keywords

Infrastructures, Resilience, Hurricane, Power, Transportation, Facebook

Abstract

Extreme events such as hurricanes can significantly disrupt infrastructures, leading to negative impacts on productivity, economy, and social wellbeing. Understanding community resilience against infrastructure disruptions in response to such events is crucial for effective preparedness, mitigation, and recovery efforts. The overarching problem addressed in this dissertation centers around enhancing community resilience against infrastructure disruptions due to hurricanes. Community resilience is defined as the ability of a community to return to normalcy following a disaster. One way to enhance community resilience is to strengthen its critical lifelines and infrastructure services (e.g., power, water, transportation, internet) and capital—to reduce the likelihood of damage through mitigation. This dissertation aims to contribute to the development of disaster preparedness and restoration efforts, ultimately fostering more resilient communities in the face of natural hazards. In this dissertation, we focus on three objectives. First, this dissertation examines the impact of Hurricane Ida on population activity using aggregate location data from Facebook. Community resilience is quantified based on changes in the number of Facebook users before, during, and after the disaster, considering both the magnitude of impact and the time to recover. Second, community resilience against infrastructure disruptions is explored through a spatio-temporal deep learning model to understand the dynamics of impacted communities against infrastructures. Third, an agent-based modeling approach is presented to enhance community resilience by simulating interdependent infrastructure systems. Interdependencies between two networks are modeled in two ways, (i) representing the role of transportation in fuel delivery to power plants and restoration teams' access, (ii) impact of power outage on transportation network. We simulate three restoration strategies: component based, distance based, and traffic lights based. Overall, findings of this dissertation underscore the importance of considering infrastructure disruptions and interdependency among infrastructure systems for enhancing community resilience against hurricanes.

Completion Date

2025

Semester

Spring

Committee Chair

Hasan, Samiul

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Department of Civil, Environmental, and Construction Engineering

Identifier

DP0029327

Document Type

Dissertation/Thesis

Campus Location

Orlando (Main) Campus

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