A State-Based Probabilistic Risk Assessment Framework for Multi-System Robotic Space Exploration 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 various combinations of failures or disruptions that may have an unpredictable impact on the mission. Existing methods of risk assessment are unable to adequately represent the interactions between systems and the progressive consequences of total or partial disruptions for these complex missions. Therefore, a state-based framework has been developed 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 (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 and mission architectures. The framework has been demonstrated for three types of analyses within the Mars Sample Return Campaign.