A State-based Probabilistic Risk Assessment Framework for Multi-system Space Missions

Modern space missions like Mars Sample Return and Artemis involve multiple systems that serve different functions. The individual failure modes of the constituent systems coupled with the complex interdependencies among them can result in a cascading effect of failures or disruptions. Risk assessment for these complex missions must consider the interactions between systems and the progressive consequences of total or partial disruptions. Therefore, a state-based framework is proposed for the probabilistic risk assessment of multi-system uncrewed space exploration missions. This hierarchical framework leverages Harel statecharts to model the operations and failure modes of individual systems. Each failure mode can be characterized by its probability of occurrence and primary consequence (e.g., delay in operations, additional cost, fatal failure, etc.). The system-level statecharts are contained within a mission-level model that connects them through logical and temporal operators to simulate functional dependencies among the systems. The double-layer (system-level and mission-level) model can be used for stochastic analysis through Monte Carlo simulations. By defining mission-level performance metrics and observing them for various mission profiles, the system-level operational risks can be related to the mission outcomes, and the mission-level impact of each failure mode can be assessed. Overall, this framework can provide deeper and richer insights by enabling sensitivity analysis, risk quantification/ranking, and comparison of various operational concepts. Our framework has been demonstrated on a part of the Mars Sample Return Program, specifically for operations ranging from sample tube retrieval to the orbital capture and containment of the sample container.