Exhaustive probabilistic risk assessment for space applications including common causes

Probabilistic Risk Assessment (PRA) is crucial in identifying causes and controls, and assessing residual risks in safety-critical industries. The Artemis mission aims to establish human safe permanence in space, necessitating adapted safety evaluation tools. NASA has led PRA complexity in space based on its manned flight history, while Europe lacks PRA standards like ECSS, despite mandatory Fault Tree Analyses (FTAs) for crewed missions. Thales Alenia Space proposes enhancing PRA modeling in FTAs by quantifying Common Cause Failure (CCF) events and integrating Safety mitigations in PRA. The proposed methodology improves estimates residual risks, with explicit CCF modeling over outdated approaches and specific tailoring for space vehicles and hazards. Proof on concepts on Gateway manned modules demonstrates benefits of this PRA approach for safety panels and industry, to minimize biases. Our results show the need for international consensus and standardizations on quantitative FTA methods for the space projects.