This study, as a follow-up to the previous work, proposes a fully automated methodology for consequence quantification (radiological dose) and F–C (Frequency–Consequence) curve generation by directly leveraging event sequence frequencies automatically calculated in the preceding study. The previous work implemented automated event sequence generation and frequency quantification by coupling a dynamic event tree analysis with the PCTRAN, where sequence frequencies were obtained by combining initiating event frequencies with event tree branch (success/failure) probabilities. This follow-up study focuses on directly coupling those frequency results with consequence quantification. Nuclear Energy Institute (NEI) 18-04 presents a Technology-Inclusive, Risk-Informed, and Performance-Based (TI-RIPB) methodology developed primarily for non-LWR reactor types, capable of providing an F–C curve based analytical framework applicable to the licensing of advanced reactors across various reactor types, including LWRs (Light Water Reactors). Because a non-LWR plant model is not currently available in the simulator environment, the Korean OPR-1000 model was adopted as the reference plant for implementing and demonstrating the proposed approach.
To enable efficient generation of the F–C curve by directly linking accident frequencies with dose-assessment results, this study develops an integrated platform by tightly coupling the nuclear power plant simulator PCTRAN with the radiological dose assessment code RadPuff. The platform employs UI-based automation and OCR-based data extraction to execute large numbers of scenarios and collect key outputs without manual intervention in a simulator environment with limited external data interfaces. After each sequence simulation in PCTRAN, the corresponding dose-related output is transferred to RadPuff, and the integrated TEDE (Total Effective Dose Equivalent) is automatically extracted. Finally, the F–C curve is automatically generated and saved as a log-scale plot by combining the final sequence frequencies (/Reactor Year) computed in the preceding study with the integrated TEDE dose results obtained from RadPuff. The proposed approach is expected to improve the efficiency, reproducibility, and consistency of result generation required for F–C-curve-based LBE selection and SSC safety classification under the NEI 18-04 framework.