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The objective of this paper is to quantify the coupling effect on the power distribution of sodium-cooled fast reactors (SFRs), specifically the European SFR. Calculations are performed with several state-of-the-art reactor physics and Multiphysics codes (TRACE/PARCS, DYN3D, WIMS, COUNTHER, and GeN-Foam) to build confidence in the methodologies and validity of results. Standalone neutronic calculations were generally in excellent agreement with a reference Monte Carlo-calculated power distribution (from Serpent). Next, the impact of coolant density and fuel temperature Doppler feedback was calculated. Reactivity coefficients for perturbations in the inlet temperature, coolant heat up and core power was shown to be negative with values of around −0.5 pcm/°C, −0.3 pcm/°C, and −3.5 pcm/%, respectively. Fuel temperature and coolant density feedback was found to introduce a roughly −1%/+1% in/out power tilt across the core. Calculations were then extended to axial expansion for cases where fuel is linked and unlinked to the clad. Core calculations are in good agreement with each other. The impact of differential fuel expansion is found to be larger for fuel both linked and unlinked to the clad, with the in/out power tilt increasing to around −4%/+2%. Thus, while broadly confirming the known result that standalone physics calculations give good results, the expansion coupling effect is perhaps more than anticipated a priori. These results provide a useful benchmark for the further development of Multiphysics codes and methodologies in support of advanced reactor calculations.

Accurate coupled neutronic-thermal-hydraulic analysis of SFRs requires an accurate calculation of the fuel-to-clad gap conductance. In this paper, the gap conductance of the ESFR-SMART MOX pins is investigated through modelling in seven independent fuel performance codes, to provide confidence in results and understand the uncertainties associated with the predictions. This paper presents a comparison of the conductance and predicted fuel temperature distribution between codes. The values produced from the codes are then combined to produce a best-estimate prediction of the gap conductance expressed as a function of nodal fuel rating and burn-up for all seven codes. A fit was applied to the data thus obtained. The spread between results is such that, to 95% confidence, conductance predictions may vary from the correlation by up to a factor of ~4. The gap conductance results show a general increase of conductance with fuel rating and burn-up, from 0.22 at 0 burn-up and 10 kW.m^(-1) to 0.45 at 0 burn-up and 50 kW.m^(-1) and to 1.00 W.?cm?^(-2).K^(-1) at 150 GWd.t^(-1) and 50 kW.m^(-1). Some spread between codes has been noted and appears to be consistent with the spread previously published. There is good agreement between codes at low burn-up for fuel temperature predictions. The spread between codes increases with burn-up due to multiple phenomena including JOG formation and clad swelling.

The ANSWERS® WIMS reactor physics code is being developed for whole core multiphysics modelling. The established neutronics capability for lattice calculations has recently been extended to be suitable for whole core modelling of Small Modular Reactors (SMRs). A whole core transport, SP3 or diffusion flux solution is combined with fuel assembly resonance shielding and pin-by-pin differential depletion. An integrated thermal hydraulic solver permits differential temperature and density variations to feedback to the neutronics calculation. This paper presents new methodology developed in WIMS to couple the core neutronics to the integrated core thermal hydraulics solver. Two coupling routes are presented and compared using a challenging PWR SMR benchmark. The first route, called GEOM, dynamically calculates the resonance shielding and homogenisation with the whole core flux solution. The second coupling route, called CAMELOT, separates the resonance shielding and pincell homogenisation from the whole core solution via generating tabulated cross sections. Both routes can use the MERLIN homogenised pin-by-pin whole core flux solver and couple to the same integrated thermal hydraulic solver, called ARTHUR. Heterogeneous differences between the neutronics and thermal hydraulics are mapped via thermal identifiers for neutronics materials and thermal regions. The ability for the integrated thermal hydraulic solver to call an external code via a Fortran-C-Python (FCP) interface is also summarised. This flexible external coupling permits one way coupling to an external fuel performance code or two way coupling to an external thermal hydraulic code.

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.