Student Name: Haya Helmy

Advisor: Dr. Dimitri Mavris

Milestone: PhD Thesis Proposal

Degree Program: Aerospace Engineering

Title: A Model-Based System-of-Systems Architecting Framework for Lunar Base Master Planning, Evaluation, and Design Space Exploration

Abstract: This research addresses the problem of architecting the lunar base system-of-systems for long-term human presence and driven by stakeholder objectives. As global space agencies, militaries, and commercial companies pursue a sustained presence on the lunar surface, there is a need to establish a physical lunar base capable of supporting scientific, commercial, and national objectives while evolving over time. However, current lunar base site plans lack a comprehensive, systematic process for planning the physical layout and do not account for spatial placement, connectivity, environmental constraints, or how the architecture will grow and adapt under changing requirements and increasing operational complexity. This work approaches the lunar base as a complex system-of-systems and develops a model-based systems architecting framework for generating, evaluating, and evolving lunar base architectures. System architecture decisions are formalized and structured to produce architecture instances through a generative process informed by urban planning practices, capturing the mapping of function to form, as well as spatial/topological and connectivity relationships among the objects of form. The framework leverages model-based systems engineering (MBSE) to capture, query, and trace architectural decisions to the resulting configurations. To enable quantitative evaluation, the framework establishes a connection between MBSE architecture models and multidisciplinary analysis and optimization (MDAO) models through a graph-based transformation mechanism, enabling architecture-specific evaluation of system interactions, resource flows, and infrastructure networks. This allows consistent evaluation of architecture performance while preserving traceability between architectural decisions and analysis results. Given the combinatorial explosion of possible architecture configurations, the design space is characterized by mixed-discrete, hierarchical decision variables and multiple conflicting objectives. To address this system architecture optimization (SAO) problem, population-based multi-objective algorithms augmented with surrogate models are used to efficiently explore the design space and converge to pareto-optimal architectures.  In all, this research establishes a repeatable and systematic methodology for lunar base master planning that integrates architecture generation, transformation for evaluation, and optimization. The methodology enables the analysis and evolution of architecture alternatives for long-term, scalable, and adaptable lunar surface infrastructure.

Date and time: 2026-04-24, 9 AM

Location: Collaborative Visual Environment (CoVE) Room in Weber Space Science and Technology Building

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Daniel Schrage, School of Aerospace Engineering
Dr. Perry Yang, School of City and Regional Planning
Dr. Jud Ready, GT Space Research Institute
Dr. Michael Balchanos, School of Aerospace Engineering
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