AE Ph.D. Thesis Proposal

 Fernando A. Morales Rivera

(Faculty advisor: Professor Dimitri Mavris)

Mesh-Adaptive Multidisciplinary Analysis and Optimization for Generalized Space Campaign Architecture Synthesis

Friday, August 21

2:00 - 5:00 p.m.

Weber, CoVE

Abstract:

The incoming era of human space exploration is characterized by a paradigm shift from performing standalone missions to the development and execution of space exploration campaigns (SECs). SECs comprise multiple interconnected systems and missions with complex multidisciplinary interactions and large decision spaces. Consequently, the development of SEC architectures requires significant early-phase design efforts to evaluate architectural alternatives and assess the impacts of design decisions on the overall campaign. However, given the scale and complexity of SEC architectures, current practices develop and evaluate different parts of a SEC architecture largely independently from one another, which can lead to design decisions that, while beneficial at the system level, are counterproductive at the SEC level.
Architecture synthesis can be considered the foundation of the space architecture evaluation process, integrating system sizing, mission analysis, and other disciplinary analyses into unified multidisciplinary analysis and optimization (MDAO) problems. Enabling the integrated evaluation of SEC architectures requires a generalized space architecture synthesis approach that is both flexible and applicable to arbitrary architecture concepts and configurations within SECs. However, existing approaches still lack sufficient generality to accommodate mission analysis within architecture synthesis for arbitrary SEC architectures of varying fidelity and complexity.
To address these gaps, this thesis proposes a generalized mission analysis approach that augments current space architecture synthesis capabilities to enable the integrated evaluation of SEC architectures. This approach consists of formulating arbitrary mission analysis as trajectory analysis problems (TAPs) within space architecture synthesis MDAO problems. Because these problems assume a consistent time discretization for the different disciplinary analyses involved, goal-oriented mesh adaptations are leveraged to solve them accurately while minimizing computational cost. This has the added benefit that the required discretization for solving TAPs accurately does not have to be known a priori and is instead determined automatically as part of the MDAO solution process.
The proposed approach is developed through two key research areas. First, the validity and effectiveness of different adaptive-mesh-MDAO approaches are evaluated for a representative space architecture synthesis problem. Second, the scalability of the different adaptive-mesh-MDAO approaches is evaluated by increasing the complexity of the representative problem.

Committee:

Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Graeme Kennedy, School of Aerospace Engineering
Dr. Kai James, School of Aerospace Engineering
Dr. Bradford Robertson, School of Aerospace Engineering
Dr. Stephen Edwards, NASA Marshall Space Flight Center