For Zoom link, contact dakota.j.thompson.th@dartmouth.edu

"The American Multi-modal Energy System: Model development with structural and behavioral analysis using hetero-functional graph theory"

Abstract

In the 21^st century, infrastructure is playing an ever greater role in our daily life. Presidential Policy Directive 21 emphasizes that infrastructure is critical to public confidence, the nation's safety, and its well-being. With global climate change demanding a host of changes across at least four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system, it is imperative to study models of these infrastructures to guide future policies and infrastructure developments. Traditionally these critical energy systems have been studied independently, usually in their own fields of study. Therefore, infrastructure data sets often lack the structural elements to describe the interdependencies with other infrastructures and the dynamic elements.

This thesis refers to the integration of the aforementioned energy infrastructures into a singular system-of-systems as the American Multi-modal Energy System (AMES) for the United States of America (USA). This work develops a structural and behavioral model of the AMES using Hetero-functional Graph Theory (HFGT) to provide an open-source dataset. Following a data driven approach and utilizing model-based systems engineering (MBSE) practices the proposed model is produced in the proposed steps:

1. First, the HFGT toolbox code base is advanced to model systems on the scale of the AMES and made open source.
2. Second, the analytical insights HFGs can provide relative to formal graphs are investigated.
3. Third, a reference architecture for the AMES is developed.
4. Fourth, the AMES reference architecture is instantiated into a structural model from which structural properties can be investigated.
5. Finally, a physically informed machine learning analysis of the AMES' socio-economic behavior is implemented to investigate the behavior of the AMES.

These proposed steps provide a reproducible and reusable structural and behavioral model of the AMES for guiding future policies and infrastructural developments to the USA’s critical energy infrastructure.

Thesis Committee

• Mark Laser (Chair)
• Amro M. Farid
• Geoffrey Parker
• Stephen Taylor

Contact

For more information, contact Theresa Fuller at theresa.d.fuller@dartmouth.edu.