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The paper defines a parameterization for the fuel-cladding gap thermal conductance in a Sodium Cooled Fast Reactor. This collaboration took place within the EU-funded ESFR-SMART project. This requires use of predictive codes that have been validated where possible against experimental data. This study relied on 7 fuel performance codes thus providing confidence in the recommended correlation. A single pin model for both the inner and outer fuel was built. The fuel was burned for 2100 Effective Full Power Days, with the axial power distribution varying over time. This paper presents a comparison between the codes’ results and a 2-D correlation for the heat conductance with respect to fuel burn-up and fuel rating. The fuel is broken down into nodes with specific fuel rating and burn-up, leading to the gap conductance expressed as a function of nodal fuel rating and burn-up. Data was then compiled for all the nodes, for both fissile and fertile regions, for both inner and outer fuel for all 7 codes. A 2D fit was applied to the data thus obtained. The results obtained show a general increase of heat conductance with fuel rating and burn-up, from 0.22 at 0 burn-up and 10 kW/m to 0.45 W/cm2K at 0 burn-up and 50 kW/m and to 1.00 W/cm2K at 150 GWd/t and 50 kW/m. Some spread between codes has been noted and appears to be consistent with the spread published earlier by several code developers. Sensitivity to various modelling assumptions is under investigation. This is aided by the use of numerous fuel performance codes which enables a wide ranging and thorough sensitivity analysis.

To improve the public acceptance of the future nuclear power in Europe we have to demonstrate that the new reactors have significantly higher safety level compared to traditional reactors. The ESFR-SMART project (European Sodium Fast Reactor Safety Measures Assessment and Research Tools) aims at enhancing further the safety of Generation-IV SFRs and in particular of the commercial-size European Sodium Fast Reactor (ESFR) in accordance with the European Sustainable Nuclear Industrial Initiative (ESNII) roadmap and in close cooperation with the Advanced Sodium Technological Reactor for Industrial Demonstration (ASTRID) program. The project aims at 5 specific objectives: Produce new experimental data in order to support calibration and validation of the computational tools for each defence-in-depth level. Test and qualify new instrumentations in order to support their utilization in the reactor protection system. Perform further calibration and validation of the computational tools for each defence-in-depth level in order to support safety assessments of Generation-IV SFRs, using the data produced in the project as well as selected legacy data. Select, implement and assess new safety measures for the commercial-size ESFR, using the GIF methodologies, the FP7 CP-ESFR project legacy, the calibrated and validated codes and being in accordance with the update of the European and international safety frameworks taking into account the Fukushima accident. Strengthen and link together new networks, in particular, the network of the European sodium facilities and the network of the European students working on the SFR technology. By addressing the industry, policy makers and general public, the project is expected to make a meaningful impact on economics, environment, EU policy and society. Selected results and milestones achieved during the first eighteen months of the project will be briefly presented, including proposal of new safety measures for ESFR; evaluation of ESFR core performance; benchmarking of codes; experimental programs; and education and training.

To improve the public acceptance of the future nuclear power in Europe we have to demonstrate that the new reactors have significantly higher safety level compared to traditional reactors. The ESFR-SMART project (European Sodium Fast Reactor Safety Measures Assessment and Research Tools) aims at enhancing further the safety of Generation-IV SFRs and in particular of the commercial-size European Sodium Fast Reactor (ESFR) in accordance with the European Sustainable Nuclear Industrial Initiative (ESNII) roadmap and in close cooperation with the Advanced Sodium Technological Reactor for Industrial Demonstration (ASTRID) program. The project aims at 5 specific objectives: Produce new experimental data in order to support calibration and validation of the computational tools for each defence-in-depth level. Test and qualify new instrumentations in order to support their utilization in the reactor protection system. Perform further calibration and validation of the computational tools for each defence-in-depth level in order to support safety assessments of Generation-IV SFRs, using the data produced in the project as well as selected legacy data. Select, implement and assess new safety measures for the commercial-size ESFR, using the GIF methodologies, the FP7 CP-ESFR project legacy, the calibrated and validated codes and being in accordance with the update of the European and international safety frameworks taking into account the Fukushima accident. Strengthen and link together new networks, in particular, the network of the European sodium facilities and the network of the European students working on the SFR technology. By addressing the industry, policy makers and general public, the project is expected to make a meaningful impact on economics, environment, EU policy and society. Selected results and milestones achieved during the first eighteen months of the project will be briefly presented, including proposal of new safety measures for ESFR; evaluation of ESFR core performance; benchmarking of codes; experimental programs; and education and training.

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.

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.

The Superph´enix SFR has been modelled using the new MERLIN flux solver module of the WIMS reactor physics code. The reactor was simulated for a range of calculation cases which investigated the neutronic effects of different temperatures and control rod insertions, for the purposes of validation against experimental data and verification against Serpent. The WIMS results were found to be in good agreement with the experimental data and the Serpent benchmark. Two different MERLIN models were constructed: a detailed hexagonal-Z geometry in 172 groups, and a hybrid method which used a simplified RZ model to condense the data used in the calculation into fewer groups before using the full hexagonal-Z geometry. This hybrid method was found to decrease the time taken for the calculations by a factor of five while retaining a good level of accuracy.

The Superph´enix SFR has been modelled using the new MERLIN flux solver module of the WIMS reactor physics code. The reactor was simulated for a range of calculation cases which investigated the neutronic effects of different temperatures and control rod insertions, for the purposes of validation against experimental data and verification against Serpent. The WIMS results were found to be in good agreement with the experimental data and the Serpent benchmark. Two different MERLIN models were constructed: a detailed hexagonal-Z geometry in 172 groups, and a hybrid method which used a simplified RZ model to condense the data used in the calculation into fewer groups before using the full hexagonal-Z geometry. This hybrid method was found to decrease the time taken for the calculations by a factor of five while retaining a good level of accuracy.

The paper defines a parameterization for the fuel-cladding gap thermal conductance in a Sodium Cooled Fast Reactor. This collaboration took place within the EU-funded ESFR-SMART project. This requires use of predictive codes that have been validated where possible against experimental data. This study relied on 7 fuel performance codes thus providing confidence in the recommended correlation. A single pin model for both the inner and outer fuel was built. The fuel was burned for 2100 Effective Full Power Days, with the axial power distribution varying over time. This paper presents a comparison between the codes’ results and a 2-D correlation for the heat conductance with respect to fuel burn-up and fuel rating. The fuel is broken down into nodes with specific fuel rating and burn-up, leading to the gap conductance expressed as a function of nodal fuel rating and burn-up. Data was then compiled for all the nodes, for both fissile and fertile regions, for both inner and outer fuel for all 7 codes. A 2D fit was applied to the data thus obtained. The results obtained show a general increase of heat conductance with fuel rating and burn-up, from 0.22 at 0 burn-up and 10 kW/m to 0.45 W/cm2K at 0 burn-up and 50 kW/m and to 1.00 W/cm2K at 150 GWd/t and 50 kW/m. Some spread between codes has been noted and appears to be consistent with the spread published earlier by several code developers. Sensitivity to various modelling assumptions is under investigation. This is aided by the use of numerous fuel performance codes which enables a wide ranging and thorough sensitivity analysis.