Monte Carlo and Bayesian-based reliability modeling of spaceborne separation control systems under radiation environment

Separation control systems are critical spacecraft subsystems responsible for irreversible operations such as stage separation and payload deployment, and are highly susceptible to radiation-induced faults in space environments. Conventional reliability assessment methods assuming constant failure rates are inadequate for such one-shot, time-dependent, and non-resettable systems. To address these challenges, this paper proposes a system-level modeling and risk analysis framework that integrates temporal state transition modeling, Monte Carlo simulation and Bayesian Network (BN). A high-fidelity SEU simulator is developed using CRÈME96 parameters and accelerator test data, incorporating a time-dependent failure rate λ ( t ) and k -bit upset events. The framework enables dynamic analysis of fault propagation and masking behaviors, identifies critical failure paths through BN, and evaluates redundancy strategies including One-hot encoding with TMR (OTMR) and Critical paths one-hot encoding with TMR (CTMR). Simulation results show that “premature activation” and “firing not executed” are the dominant failure modes, and the path importance of critical failure paths varies under different fault injection intensities. The proposed OTMR and CTMR schemes improve system reliability by 44.5% and 30.1% over Single Module (SM) designs, Moreover, selective reinforcement of critical paths proves effective under resource constraints. This work provides a systematic framework for SEU risk analysis and robust design, offering valuable insights for radiation-hardened protection in spaceborne systems.