Disaggregated space system conceptual design optimization - Stochastic analysis methods

A methodology for the optimization of disaggregated space systems dubbed Disaggregated Integral System Concept Optimization (DISCO) has previously been proposed. The DISCO methodology was applied to multi-orbit and multi-function/multi-orbit disaggregation problems. The performance and resilience of these architectures is dependent upon stochastic variables such as environmental variations, satellite failure rates, and launch vehicle failure rates. This paper introduces techniques for assessing the impacts of these stochastic parameters on optimized space system conceptual designs, and their associated lifecycle costs. Previous analysis was performed identifying cost effective Disaggregated Weather System Follow-on (DWSF) conceptual architectures. The analysis techniques introduced in this paper are also applied to DWSF. This application demonstrates that the identified minimum cost solution is also the minimum cost risk solution for empirically derived satellite and launch vehicle failure rates. Initial results also indicate that the identified DWSF solution is very robust to significant reductions in satellite and launch vehicle reliability parameters. Conceptual design considerations gleamed from the applied stochastic analysis techniques are then discussed along with the broader implications on small satellite constellation designs and small satellite access to space.