Uncertainty analysis of UAM TMI-1 benchmark by STREAM/RAST-K
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This study rigorously examined uncertainty in the TMI-1 benchmark within the Uncertainty Analysis in Modeling (UAM) benchmark suite using the STREAM/RAST-K two-step method. It presents two pivotal advancements in computational techniques: (1) Development of an uncertainty quantification (UQ) module and a specialized library for the pin-based pointwise energy slowing-down method (PSM), and (2) Application of Principal Component Analysis (PCA) for UQ. To evaluate the new computational framework, we conducted verification tests using SCALE 6.2.2. Results demonstrated that STREAM’s performance closely matched SCALE 6.2.2, with a negligible uncertainty discrepancy of ±0.0078% in TMI-1 pin cell calculations. To assess the reliability of the PSM covariance library, we performed verification tests, comparing calculations with Calvik’s two-term rational approximation (EQ 2-term) covariance library. These calculations included both pin-based and fuel assembly (FA-wise) computations, encompassing hot zero-power and hot full-power operational conditions. The uncertainties calculated using both the EQ 2-term and PSM resonance treatments were consistent, showing a deviation within ±0.054%. Additionally, the data compression process yielded compression ratios of 88.210% and 92.926% for on-the-fly and data-saving approaches, respectively, in TMI fuel assembly calculations. In summary, this study provides a comprehensive explanation of the PCA process used for UQ calculations and offers valuable insights into the robustness and reliability of newly developed computational methods, supported by rigorous verification tests.
Abstract
This study rigorously examined uncertainty in the TMI-1 benchmark within the Uncertainty Analysis in Modeling (UAM) benchmark suite using the STREAM/RAST-K two-step method. It presents two pivotal advancements in computational techniques: (1) Development of an uncertainty quantification (UQ) module and a specialized library for the pin-based pointwise energy slowing-down method (PSM), and (2) Application of Principal Component Analysis (PCA) for UQ. To evaluate the new computational framework, we conducted verification tests using SCALE 6.2.2. Results demonstrated that STREAM’s performance closely matched SCALE 6.2.2, with a negligible uncertainty discrepancy of ±0.0078% in TMI-1 pin cell calculations. To assess the reliability of the PSM covariance library, we performed verification tests, comparing calculations with Calvik’s two-term rational approximation (EQ 2-term) covariance library. These calculations included both pin-based and fuel assembly (FA-wise) computations, encompassing hot zero-power and hot full-power operational conditions. The uncertainties calculated using both the EQ 2-term and PSM resonance treatments were consistent, showing a deviation within ±0.054%. Additionally, the data compression process yielded compression ratios of 88.210% and 92.926% for on-the-fly and data-saving approaches, respectively, in TMI fuel assembly calculations. In summary, this study provides a comprehensive explanation of the PCA process used for UQ calculations and offers valuable insights into the robustness and reliability of newly developed computational methods, supported by rigorous verification tests.
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