Matching high ambitions with scarce resources is one of the primary challenges of the aerospace industry, on par with the technical challenges of developing new technology. The challenge is further complicated in space exploration, by its own nature aimed at exploring the unknown. Stakeholder objectives are often unclear due to business cases highly exploratory in nature. Further ambiguity emerges from disagreement between stakeholders and decision-makers called to formulate scientific, technological and policy requirements for new systems. This thesis develops a structured approach to develop recommendations to system architects concerned with the design of unprecedented large aerospace infrastructures for which objectives are ambiguous or unclear. The approach is composed of three parts. The first part consists in a novel taxonomy of ambiguity in systems design that classifies ambiguities in reducible and irreducible components. Building on this taxonomy, the second part of this thesis develops a Descriptive Systems Architecting Management Framework (SA-MF) to distill canonical forms of ambiguity management from the literature in political science, finance and economics, management, and engineering design. The third part of the dissertation presents a Delphi-Based Systems Architecting Framework (DB-SAF). DB-SAF objectives are to identify sources of ambiguity in the value delivery and tradespace exploration processes, characterize and model sources of ambiguity, mitigate ambiguities through effective systems architecting strategies, integrate the analysis of upstream and downstream architecting processes, and to assess the impact of requirement ambiguities on the architectural tradespace. The proposed systems architecting approach has been applied to three case studies: the assessment of a robotic Mars Sample Return Campaign, the study of in-space transportation infrastructure for future human space exploration beyond Low Earth Orbit, and the retrospective analysis of satellite constellations for commercial applications. The application of the proposed approach to three different disciplinary fields demonstrates its broad applicability for architecting complex aerospace systems. This dissertation integrates methods from systems engineering, systems architecting, multivariate statistical analysis, uncertainty modeling, economics, management science and social science research. It allows decision-makers to visualize an architectural synthesis of aerospace systems, understanding adverse impacts of ambiguity, and supporting negotiations among stakeholders for efficient compromise in systems architecting.
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