Uncertain input parameter sample combinations database

The study of physical process failure is the core link of passive system failure research. This study focuses on the Secondary side Passive Residual Heat Removal System (PRS) of HPR1000, and constructs a small sample uncertainty parameter screening mechanism that integrates Failure Mode and Effects Analysis (FMEA) and parameter correlation analysis. With the help of FMEA, 24 uncertain input parameters were accurately determined, and the ASYST program was used to quantitatively transfer uncertainty to the A group of small samples (100 groups) generated by Latin hypercube sampling. Combined with parameter correlation analysis, 11 high impact parameters were successfully identified, and the consistency of the results was verified by analyzing the B group of large samples (10000 groups). Research has shown that this small sample screening strategy has both efficient and reliable advantages in screening uncertain parameters of passive safety systems. This achievement provides theoretical support and technical reference for the quantification of uncertainty and reliability design optimization of passive systems.