Abstract
In the design of a spent nuclear fuel disposal system, one necessary condition is to show that the configuration remains subcritical at time of emplacement but also during long periods covering up to 1,000,000 years. In the context of criticality safety applying burn-up credit, k-eff eigenvalue calculations are affected by nuclear data uncertainty mainly in the burnup calculations simulating reactor operation and in the criticality calculation for the disposal canister loaded with the spent fuel assemblies. The impact of nuclear data uncertainty should be included in the k-eff value estimation to enforce safety. Estimations of the uncertainty in the discharge compositions from the CASMO5 burn-up calculation phase are employed in the final MCNP6 criticality computations for the intact canister configuration; in between, SERPENT2 is employed to get the spent fuel composition along the decay periods. In this paper, nuclear data uncertainty was propagated by Monte Carlo sampling in the burn-up, decay and criticality calculation phases and representative values for fuel operated in a Swiss PWR plant will be presented as an estimation of its impact.
Highlights
A summarized result of which spent nuclear fuel assemblies can be loaded into the final disposal canister, fulfilling the regulatory limit from the criticality safety point of view, is usually collected in the form of loading curves.Together with the regulatory limit, the biases and uncertainties in the calculation methodology employed to generate those curves are included
Without considering degradation issues or damages that could occur during the considered geological periods, the loaded canister is assumed to be flooded with water entering through a postulated breach
A 35 cm layer of water saturated bentonite clay is included in the model; its impact on the results will be negligible for the flooded conditions problem
Summary
A summarized result of which spent nuclear fuel assemblies can be loaded into the final disposal canister, fulfilling the regulatory limit from the criticality safety point of view, is usually collected in the form of loading curves.Together with the regulatory limit, the biases and uncertainties in the calculation methodology employed to generate those curves are included. The tools employed to propagate the uncertainties in the different steps of the methodology are all based on the Monte Carlo method and briefly described in the paper
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