2026-09-22T15:06:50Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/129312 2025-10-20 col_2142_5131 col_2142_14800 com_2142_5130 com_2142_14799 com_2142_234

application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms The student, Richard Eason, accepted the attached license on 2025-05-02 at 15:37. The student, Richard Eason, submitted this Thesis for approval on 2025-05-02 at 15:39. This Thesis was approved for publication on 2025-05-06 at 09:16. DSpace SAF Submission Ingestion Package generated from Vireo submission #22191 on 2025-10-19 at 18:12:20 Mission design analysis methodology for space-based computational data centers Eason, Richard 2025-05-06 Lembeck, Michael Space systems space-based datacenters space-based compute mission design FreeFlyer Design analysis Simulation data center eng The increasing volume and rate of data generated by Earth observation and other satellite constellations present significant challenges to traditional ground-based processing paradigms, primarily due to downlink bandwidth limitations and latency constraints. This thesis investigates the emerging concept of shifting computational tasks to orbit, utilizing dedicated space-based data center platforms networked with sensor spacecraft. Such distributed architectures offer potential benefits, including reduced data downlink requirements, lower latency for time-critical applications, and leveraging of in-space resources like solar power. However, designing these complex mission architectures involves navigating numerous interdependent technical and economic trade-offs across the ”system of systems”. To address this, a mission design analysis methodology centered around a high-fidelity simulation tool developed within the a.i. Solutions’ FreeFlyer environment is presented. This simulator models the dynamic interactions between key spacecraft subsystems—including electrical power, thermal management, communications (inter-satellite and space-to-ground), propulsion, orbital mechanics, and data generation/processing payloads across both data-generating and data-processing spacecraft roles. The tool enables the evaluation of various architectural configurations and operational scenarios, facilitating the analysis of design parameter sensitivities, assessment of trade-offs (e.g., centralization vs. distribution, power allocation, thermal rejection), and optimization of system performance against metrics like data throughput, latency, and mass-to-orbit. This work provides a framework and a quantitative tool intended to aid mission design engineers in the systematic design and analysis of future space-based computational data center missions. 2025-05 Thesis https://hdl.handle.net/2142/129312 Copyright 2025 Richard Eason Aerospace Engineering Aerospace Engineering University of Illinois Urbana-Champaign M.S. Thesis