Abstract
In this study, the Best Estimate Plus Uncertainty (BEPU) approach is developed for the systematic quantification and propagation of uncertainties in the modelling and simulation of lead-cooled fast reactors (LFRs) and applied to the demonstration LFR (DLFR) initially investigated by Westinghouse. The impact of nuclear data uncertainties based on ENDF/B-VII.0 covariances is quantified on lattice level using the generalized perturbation theory implemented with the Monte Carlo code Serpent and the deterministic code PERSENT of the Argonne Reactor Computational (ARC) suite. The quantities of interest are the main eigenvalue and selected reactivity coefficients such as Doppler, radial expansion, and fuel/clad/coolant density coefficients. These uncertainties are then propagated through safety analysis, carried out using the MiniSAS code, following the stochastic sampling approach in DAKOTA. An unprotected transient overpower (UTOP) scenario is considered to assess the effect of input uncertainties on safety parameters such as peak fuel and clad temperatures. It is found that in steady state, the multiplication factor shows the most sensitivity to perturbations in 235U fission, 235U ν, and 238U capture cross sections. The uncertainties of 239Pu and 238U capture cross sections become more significant as the fuel is irradiated. The covariance of various reactivity feedback coefficients is constructed by tracing back to common uncertainty contributors (i.e., nuclide-reaction pairs), including 238U inelastic, 238U capture, and 239Pu capture cross sections. It is also observed that nuclear data uncertainty propagates to uncertainty on peak clad and fuel temperatures of 28.5 K and 70.0 K, respectively. Such uncertainties do not impose per se threat to the integrity of the fuel rod; however, they sum to other sources of uncertainties in verifying the compliance of the assumed safety margins, suggesting the developed BEPU method necessary to provide one of the required insights on the impact of uncertainties on core safety characteristics.
Highlights
In the past two decades, a renewed interest has surfaced in Generation IV lead/lead-bismuth cooled fast reactors (LFRs)
Observed differences in eigenvalues from heterogeneous Monte Carlo and homogenized MCC-3.1/DIF3D calculations are attributed to differences in cross section generation and modelling capabilities of the two codes [10, 13]
A comparison of BOC core power distribution and assembly flux is shown in Figures 7 and 8, which show the relative error is less than 10% for most assemblies. e Monte Carlo relative statistical error from Serpent for all flux and power values is in the order of 10−3
Summary
In the past two decades, a renewed interest has surfaced in Generation IV lead/lead-bismuth cooled fast reactors (LFRs). Insufficient experimental data challenges the trustworthiness of numerical results and accentuates the need for input uncertainty analysis in modelling. Evaluation of these uncertainties provides a better understanding of their impact on the reactor core design and identification of design safety limits. The Total Monte Carlo (TMC) approach assessed the effect of uncertainties originating from lead and plutonium isotopes cross sections on core parameters including criticality and coolant void worth. Nuclear data uncertainties from ENDF/B-VII.0 cross section libraries are propagated through multiple scales of reactor modelling including lattice, full core, and system level. Nuclear data uncertainties are propagated through the system model as standard deviations associated with respective feedback coefficients, which are perturbed using stochastic sampling approach to assess core safety capabilities
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