Wang, Xi has requested to schedule their PhD Thesis Final Examination (Defense). This request has been approved by their faculty advisor, the AE Associate Chair for Graduate Programs, and the AE Communications Office. Please proceed to post the annoucement on the OGE website. The details are as follows:

Student Name: Xi Wang

Advisor: Dr. Dimitri Mavris

Milestone: PhD Thesis Final Examination (Defense)

Degree Program: Aerospace Engineering

Title: Integrated Parametric Optimization Framework for Designing UAM Network and Supporting Infrastructure to Increase Network Efficiency

Abstract: Urban areas worldwide are facing mounting challenges of traffic congestion and greenhouse gas emissions as traditional ground transportation systems struggle to meet increasing travel demand. Urban Air Mobility (UAM), enabled by electric vertical take-off and landing (eVTOL) aircraft, presents a promising alternative capable of alleviating congestion, improving travel times, and reducing emissions by operating in the underutilized urban airspace. However, realizing this vision requires innovative methods to design, validate, and integrate UAM networks with existing urban and energy infrastructures. This dissertation develops an integrated design methodology that unifies transportation network planning with electric grid analysis to enable the sustainable deployment of UAM systems. The framework combines agent-based multimodal transportation simulations with high-fidelity electric power flow models to evaluate how UAM operations interact with both ground transportation and local electrical grids. Through this integrated approach, the research identifies optimal vertiport locations, network configurations, and charging infrastructure layouts that improve overall mobility performance while maintaining grid reliability and efficiency. As a novel mode of transportation, UAM lacks the historical operational data required by traditional grid analysis frameworks. To overcome this limitation, the methodology dynamically generates charging demand profiles from agent-based simulations rather than relying on fixed schedules, capturing real-time traveler behavior and its impact on energy systems. It further investigates the integration of distributed energy resources such as photovoltaic (PV) generation and battery energy storage (BESS), to enhance grid hosting capacity, reduce peak demand, and improve sustainability. The results demonstrate improvements in multimodal travel efficiency and emission reduction, while also establishing a robust method for quantifying the electric grid’s capability to support eVTOL charging. By embedding grid constraints directly into transportation network design, this research introduces a cross-domain methodology that co-optimizes mobility and energy systems. Ultimately, the proposed methodology provides a scalable analysis method for planners, policymakers, and industry stakeholders to design resilient, energy-aware, and sustainable UAM networks that can be effectively integrated into the future urban landscape. 

Date and time: 2025-11-06, 9am

Location: Weber CoVE

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Daniel Schrage, School of Aerospace Engineering
Dr. Perry Pei-Ju Yang, School of City & Regional Planning and Architecture
Dr. Michael Balchanos, School of Aerospace Engineering
Dr. Ahmed Mohamed, GridBridge