As in other nuclear countries, the operation of the Ignalina nuclear power plant in Lithuania has led to the accumulation of around 22 thousand assemblies of spent nuclear fuel (SNF). The development of geological disposal program involves an iterative assessment of the system safety supported by scientific research on radionuclides migration and related processes. This study focused on the application of Contribution to the Sample Mean (CSM) and Contribution to Sample Variance (CSV) methods to complement the uncertainty and sensitivity analyses of the time-dependent flux of I-129 from the engineered barriers of a conceptual disposal facility for RBMK-1500 SNF (RBMK is abbreviation of "High Power Channel-type Reactor" (in Russian)). The analysis was performed using a MATLAB platform (8.0.0.783 (R2012b), MathWorks, MA, USA). The mean and variance ratios derived from CSM and CSV plots were applied to estimate the effect of reduced uncertainty range on mean flux and its variance, and the uncertainty analysis was also complimented. Increasing the lower bounding value of defect size enlargement time range to 4.6 × 10 4 years would lead to a lower mean flux until 5 × 10 4 years after repository closure. Later on (up to 1 million years after repository closure), the only reduction of the upper bounding value of the SNF dissolution rate range would affect a decreased mean flux.Keywords: RBMK-1500 spent nuclear fuel; deep geological repository; uncertainty and sensitivity; CSM; CSV; radionuclide migration 3 × 10 −12 (p = 0.15) 1 × 10 −11 (p = 0.7) 3 × 10 −11 (p = 0.15) Discrete 1 Probability density function. SNF: spent nuclear fuel.Minerals 2019, 9, 521 5 of 26
Characterization of Model BehaviorThe model realized using the computer code AMBER [34] assessed time-dependent radionuclide release from the SNF matrix, dissolution, radioactive decay, and contaminant transport by diffusion through engineered barriers. The uncertainty of the main transport-related parameters, including defect size enlargement time, was characterized by probability density function for each parameter. The model output was a large number of the time-dependent flux values over an extended period (10 3 -10 6 years after repository closure), which allowed for the evaluation of the mean flux, the quantiles, and the distribution of the peak flux, as illustrated in Figure 2.