Uncertainty Propagation for LWR Burnup Benchmark Using Sampling Based Code Scale/Sampler

Abstract

Abstract.Sampling based method is adopted in many fields of engineering and it is currently used to propagate uncertainties from physical parameters and from nuclear data, to integral indicators of nuclear systems. The total uncertainty associated with a model simulation is of major importance for safety analysis and to guide vendors about acceptable tolerance limits for nuclear installations parts. This work presents some calculations to propagate uncertainties for a nuclear reactor fuel element modeled in SCALE/TRITON, using the sampling tool SCALE/SAMPLER. Results showed that the influence of input uncertainties on k inf is more pronounced in the fresh core other than the depleted core and the contribution from studied manufacturing uncertainties is smaller than the contribution of nuclear data uncertainties.

Nuclear Data Covariance Analysis in Radiation-Transport Simulations Utilizing SCALE Sampler and the IRDFF Nuclear Data Library

“…The methodology utilized by the Sampler employs a multivariate normal distribution with negative values truncated [18]. The impact from choosing a normal distribution with negative value rejection is mitigated, because uncertainties are generally larger in regions where the reaction cross section is lower, so the net result on the problem may be reduced.…”

“…The impact to this research is that an estimation of the uncertainty is determined. The quality of that estimation is high for well-studied cross sections and diminishes as the nuclear data uncertainty increases and is a fundamental limitation of current methodologies [5], [18].…”

“…Evaluated uncertainties may also be the underestimates of the general nuclear data uncertainty [17]. Capturing the full nuclear data uncertainty is essential, because it is often a dominant unknown in the nuclear applications [18]. Furthermore, every reaction and uncertainty of interest may not be available in the same nuclear data library, which motivates a need to include additional libraries to meet the experimental modeling requirements.…”