Student Name: Victor Yang

Advisor: Dr. Dimitri Mavris

Milestone: PhD Thesis Final Examination (Defense)

Degree Program: Aerospace Engineering

Title: A Design Methodology For Resilient Cislunar Space Domain Awareness Architectures

Abstract: Cislunar space is the next frontier of human space exploration as scientific and commercial missions by national agencies and private entities are driving a renewed race to the Moon. Long-term human presence in this domain depends on supporting infrastructure, of which space domain awareness is a critical component that tackles the detection, tracking, and identification of space objects. SDA has been crucial for near-Earth applications, and the same need will follow as activity in cislunar space grows. Systems resilience as developed for terrestrial infrastructure and for space mission success motivates this work on resilient SDA design. Traditional design processes consider resilience analysis as robustness or disruption analysis after the conceptual design phase, when high-level performance and cost trades are already conducted. Layering resilience onto fixed architectures yields a narrow solution space and weak traceability between resilience outcomes and design decisions. The core technical barrier that blocks resilience from entering the conceptual phase is the modeling complexity of resilience evaluation, where it must be concretely defined, simulated, and measured rapidly enough to participate within the optimization loop. This thesis develops a methodology that brings system-of-systems resilience into the conceptual design of cislunar SDA architectures through a phase-based performance framework, with three research questions derived from the technical gaps. First, a flow-weighted supra-adjacency matrix (FW-SAM) was developed as a graph-based replacement for discrete-event DTN simulation. Encoding sensing, communication, and relay flow in a single sparse matrix, the FW-SAM evaluates downlink efficiency directly from its structure. The second research question addresses graph-based robustness metrics, with sensor performance loss, downlink efficiency loss, and relay efficiency impact derived directly from the FW-SAM. The third research question formulates an analytic resilience integral combining preemption probability, robustness, recovery time, and an adaptation trajectory with a phase-decomposed cost model, where the integral couples resilience investment to the architecture being designed. The validated methods are composed into a multi-objective optimization spanning constellation architecture and resilience phase variables. All-in-One Integrated Resilience Optimization (AIRO) jointly optimizes all variables with, tested against two sequential baselines, with and without resilience optimization. AIRO produced wider Pareto spread on all three objectives and discovered more than twice the architecture classes of the sequential approach, including constellations with lower sensor capability paired with high adaptation investment that the sequential methods cannot find. The resilience objective also drove orbit diversity beyond what performance and cost optimization together could produce. The graph surrogate, the analytic resilience integral, and the architecture-coupled cost model make resilience tractable inside the computational budget of evolutionary optimization, enabling enhanced resilience tradespace exploration for future cislunar SDA systems. 

Date and time: 2026-04-24, 1:30 PM

Location: Code/Cove

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Brian Gunter, School of Aerospace Engineering
Dr. Kyriakos Vamvoudakis, School of Aerospace Engineering
Dr. Michael Balchanos, chool of Aerospace Engineering
Dr. Michael Steffens, Draper Laboratory
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