Thermodynamic resilience and vulnerability migration in closed Brayton cycle nuclear power systems: An advanced transient exergy analysis under typical malfunction scenarios

The escalating energy requirements of deep space exploration necessitate resilient nuclear power systems, where gas-cooled reactors coupled with a closed Brayton cycle offer a high-power-density solution. To overcome conventional assessment limitations, this study establishes a fully verified dynamic exergy evaluation framework. By integrating advanced exergy analysis with the objective Entropy Weight Method, the research quantifies irreversibility evolution under reactivity-induced power offset, turbomachinery performance degradation, radiator partial failure and combined reactivity-turbomachinery failure. Results demonstrate that while the heat rejection subsystem dominates steady-state exergy destruction (>91%), thermodynamic bottlenecks shift drastically during perturbations. Specifically, turbomachinery, radiator and combined malfunctions trigger a massive migration of vulnerability to the regenerator, where exergy destruction rates surge by 800.8%, 273.9%, and 379.2% respectively. Advanced decomposition reveals over 75% of these surges are avoidable exogenous losses, suggesting the regenerator severe systemic thermal fluctuations. Sensitivity analysis reveals a thermodynamic duality: the regenerator exhibits a tendency to act as a primary thermodynamic bottleneck independent of space sink temperatures and predefined component design margins during non-heat-source and compounding malfunctions, whereas heat-source malfunction exhibit environment-dependent vulnerability. Furthermore, robustness assessments identify maximum system fragility during Brayton subsystem and combined multi-subsystem malfunctions. These findings provide critical quantitative guidance for resilient space reactor designs, suggesting engineering efforts must prioritize regenerator thermal buffering and adaptive turbomachinery aerodynamic matching to promote potential operational stability.