Human Reliability Analysis (HRA) is a systematic approach used to estimate Human Error Probability (HEP) by evaluating human actions and modeling human performance within a system context. It is a critical component of Probabilistic Safety Assessment (PSA) for nuclear power plants because human actions significantly affect accident prevention and mitigation. Various HRA methodologies have been developed and applied worldwide to support PSA. However, differences in theoretical foundations and quantification procedures may lead to divergent results when applied to the same scenario. Such variability can affect the consistency and credibility of PSA outcomes. Therefore, a systematic comparative study of HRA methods is necessary to enhance the reliability and robustness of PSA results. This study presents qualitative and quantitative comparisons between IDHEAS-ECA, a modern methodology applicable to comprehensive HRA analyses, and K-HRA, the current standard method used in domestic PSA practices in Korea. IDHEAS-ECA is based on the NUREG-2114 cognitive model and incorporates Cognitive Failure Modes (CFMs) and Performance Influencing Factors (PIFs), whereas K-HRA relies on the Stimulus–Organism–Response (SRO) model and classifies errors into diagnosis and execution errors. These methodological differences may influence HEP estimation. For the quantitative comparison, 34 post-initiator human failure events from the full-power internal event PSA of NPPs for the FRAMATOME were analyzed. Although tendencies vary across individual HFEs,
IDHEAS-ECA generally yields lower HEP estimates than K-HRA, likely due to its consideration of multiple Cognitive Failure Modes (CFMs) for each critical task as task complexity increases. This study qualitatively and quantitatively compares IDHEAS-ECA and K-HRA to support the selection of appropriate HRA methodologies. Both methods were applied to full-power internal events at NPPs for the FRAMATOME, and the results show that HEP estimates are influenced by task complexity and vary by methodology. These findings provide useful guidance for selecting HRA methods and estimating HEP in PSA.