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There is a general consensus that Mars is the next high priority destination for human space exploration. There has been no lack of analysis and recommendations for human missions to Mars, including, for example, the NASA Design Reference Architectures and the Mars Direct proposal. These studies and others usually employ the traditional approach of selecting a baseline mission architecture and running individual trade studies. However, this can cause blind spots, as not all combinations are explored. An alternative approach is to holistically analyze the entire architectural trade-space such that all of the possible system interactions are identified and measured. In such a framework, an optimal design is sought by minimizing cost for maximal value. While cost is relatively easy to model for manned spaceflight, value is more difficult to define. In our efforts to develop a surface base architecture for the MIT Mars 2040 project, we explored several methods for quantifying value, including technology development benefits, challenge, and various metrics for measuring scientific return. We developed a science multi-score method that combines astrobiology and geologic research goals, which is weighted by the crew-member hours that can be used for scientific research rather than other activities.

Engineering changes and their propagation through a system provide insight into the complexity of a system. In an effort to identify systematic trends, we have analyzed two very different JPL-led space mission projects to classify the change activity and assess change propagation. The projects selected are a Mars lander mission, Mars Science Laboratory (MSL), and an Earth-orbiting mission, Soil Moisture Active Passive (SMAP). Change in space system development is recorded with engineering change requests (ECRs). ECRs can be regarded as an indicator of the progression of work. We employ time analysis of ECR initiation throughout the lifecycle, correlate ECR generators with ECR absorbers, and consider the distribution of ECRs across subsystems. Further, we analyze ECR-document and ECR-ECR networks to assess project interaction. These analyses give us insight into the similarities and differences between these projects. For both SMAP and MSL, similar subsystems generate or absorb change. However, SMAP followed a progression in which change was damped over time, whereas MSL often saw acceleration of change. The two projects also differed with regard to change management, with SMAP using a hierarchical approach while MSL interactions were more widely distributed.