Date of Award

2025-08-01

Degree Name

Doctor of Philosophy

Department

Mechanical Engineering

Advisor(s)

Sergio A. Fong

Abstract

Ineffective systems engineering practices continue to jeopardize aerospace missions, resulting in multi-billion-dollar losses, delays, and fragmented development outcomes. As complexity intensifies and timelines shrink, conventional document-based methods increasingly fail to support early validation, cross-domain traceability, and synchronized tool usage. This research presents an integrated approach that addresses three critical gaps: synchronizing executable and traceable MBSE models across structural, behavioral, and requirements domains; applying scalable requirements prioritization techniques tailored for Complex Adaptive Systems; and establishing automated simulation feedback loops through digital toolchain integration. Central to this strategy is the Digital Trinity, which connects system models, simulations, and lifecycle data through a continuous digital thread. The proposed methodology begins with SysML-based modeling in Cameo Systems Modeler, followed by a multi-phase prioritization process using filtration, metadata scoring, and comparative weighting to evaluate over one hundred mission requirements. The approach is applied to the SidSat mission, a 4U CubeSat featuring a modular architecture with core avionics, a robotic arm payload, and an onboard AI/ML experimentation module. Requirements were allocated to model components, then verified using parameterized simulations. MATLAB was employed for mass, power, and thermal margin calculations; STK for orbital behavior assessment; Excel for value propagation and I/O management; and Teamcenter with AWS for model control and data traceability. Simulation outputs were dynamically linked to SysML constraint blocks and displayed through interactive dashboards in Cameo, ensuring transparency of compliance and coherence of the architecture state. Results demonstrate enhanced early-stage validation, improved stakeholder alignment, and reduced risk of misalignment between model logic and simulated performance. The final system model operates as a live digital reference across design and analysis phases, enabling iterative updates and real-time feedback. Although demonstrated on a CubeSat platform, the framework is extensible to larger systems where agility, traceable decision-making, and model-simulation convergence are essential for mission assurance.

Language

en

Provenance

Received from ProQuest

File Size

361 p.

File Format

application/pdf

Rights Holder

Iqtiar Md Siddique

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