Investigation and improvement of the Mini-Max Polynomial Approximation method for solving burnup equations

Zhang, Cong; Zhang, Binhang; Bi, Yanzhao; Yuan, Xianbao; Zhang, Yonghong; Tang, Hongting

doi:10.1016/j.anucene.2022.109482

Cited by 3 publications

(1 citation statement)

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“…Even with the adoption of a coupled diffusion-depletion calculation process and the comprehensive tracking of the fuel assembly position throughout the cycles, it remains challenging to fully account for the actual depletion process of the fuel assembly in the reactor. Moreover, because the depletion calculation requires the decomposition of the burnup chain and the selection of an effective numerical calculation method to obtain the spent-fuel composition at a specific burnup [15], the approximation introduced by the burnup chain decomposition and the inherent error of the numerical calculation method make it difficult to obtain an accurate nuclear fuel composition for the depletion calculation [16,17]. Hence, when the BUC technique is applied, it is essential to analyze the spent-fuel composition used in the depletion calculation in a reasonable and conservative manner and quantify the nuclide concentration uncertainties in the criticality calculation.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis Study of Effects of Nuclide Concentration Uncertainties on Biases and Bias Uncertainties in Criticality Calculation Method

Ni,

Chen,

Xie

et al. 2023

Energies

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To quantify the uncertainties propagating from the fuel depletion calculation to the criticality calculation in the burnup credit system, this paper evaluates the effects of the nuclide concentration uncertainty on the criticality calculation based on Monte Carlo uncertainty sampling methods, and analyzes the assumption that the measured-to-calculated nuclide concentration ratio obeys a normal distribution with uncorrelation among isotopes in the Monte Carlo uncertainty sampling method by using the sensitivity and uncertainty analysis method and the Latin hypercube sampling method. The results indicated that the Monte Carlo uncertainty sampling method could effectively quantify the uncertainties with a calculation accuracy within 3%, and the criticality uncertainty calculation for the assumption that the measured-to-calculated concentration ratios obey normal distributions was more conservative than that of the samples according to their actual distributions. Thus, the assumption of a normal distribution is reasonable in the sampling process. Moreover, the uncertainty results of the criticality calculation considering the correlations among important isotopes presented a decrease of approximately 5% over those without the isotopic correlations. Therefore, introducing the correlations of significant isotopes could reduce the uncertainty of the criticality calculation for spent-nuclear-fuel storage systems.

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Section: Introductionmentioning

confidence: 99%