Abstract

For liquid metal-cooled fast reactors (LMFRs), improved predictive modelling is desirable to facilitate reactor licensing and operation and move towards a best estimate plus uncertainty (BEPU) approach. A key source of uncertainty in fast reactor calculations arises from the underlying nuclear data. Addressing the propagation of such uncertainties through multiphysics calculations schemes is therefore of importance, and is being addressed through international projects such as the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark. In this paper, a methodology for propagation of nuclear data uncertainties within WIMS is presented. Uncertainties on key reactor physics parameters are calculated for selected SFR-UAM benchmark exercises, with good agreement with previous results. A methodology for coupled neutronic-thermal-hydraulic calculations within WIMS is developed, where thermal feedback is introduced to the neutronic solution through coupling with the ARTHUR subchannel code within WIMS and applied to steady-state analysis of the Horizon 2020 ESFR-SMART project reference core. Finally, integration of reactor physics and fuel performance calculations is demonstrated through linking of the WIMS reactor physics code to the TRAFIC fast reactor fuel performance code, through a Fortran-C-Python (FCP) interface. Given the 3D multiphysics calculation methodology, thermal-hydraulic and fuel performance uncertainties can ultimately be sampled alongside the nuclear data uncertainties. Together, these developments are therefore an important step towards enabling propagation of uncertainties through high fidelity, multiphysics SFR calculations and hence facilitate BEPU methodologies.

Highlights

  • For liquid metal-cooled fast reactors (LMFRs), improved predictive modelling is desirable to facilitate reactor licensing and operation and move towards a best estimate plus uncertainty (BEPU) approach

  • This paper presents developments towards extending this capability for multiphysics analysis of fast reactors under uncertainty

  • The power distribution at EOEC in the ESFR-SMART core is first calculated without thermal feedback, and is in excellent agreement with results from the continuous energy Monte Carlo code Serpent [15] with an rms discrepancy of 0.7%, and a maximum discrepancy. k-eff from WIMS agrees to within ~200 pcm of the Serpent value

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Summary

Introduction

For liquid metal-cooled fast reactors (LMFRs), improved predictive modelling is desirable to facilitate reactor licensing and operation and move towards a best estimate plus uncertainty (BEPU) approach. This is important for innovative reactor designs (e.g. axially heterogeneous cores) for which experimental data may be more limited. The ESFR-SMART Horizon 2020 project aims at enhancing the safety of SFRs, in particular the commercial size ESFR concept [5] To this end, a reference 3600 MWth core is defined with 504 fuel assemblies, inner and outer fuel zoning, lower axial blanket and upper sodium plenum. Within ESFR-SMART, simulations with coupled spatial neutronics and thermalhydraulics codes are being performed to provide a realistic temperature distribution within the core, using parameterized multigroup cross sections

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