Nuclear energy is presently the single major low-carbon electricity source in Europe and is overall expected to maintain (perhaps eventually even increase) its current installed power from now to 2045. Long-term operation (LTO) is a reality in essentially all nuclear European countries, even when planning to phase out. New builds are planned. Moreover, several European countries, including non-nuclear or phasing out ones, have interests in next generation nuclear systems. In this framework, materials and material science play a crucial role towards safer, more efficient, more economical and overall more sustainable nuclear energy. This paper proposes a research agenda that combines modern digital technologies with materials science practices to pursue a change of paradigm that promotes innovation, equally serving the different nuclear energy interests and positions throughout Europe. This paper chooses to overview structural and fuel materials used in current generation reactors, as well as their wider spectrum for next generation reactors, summarising the relevant issues. Next, it describes the materials science approaches that are common to any nuclear materials (including classes that are not addressed here, such as concrete, polymers and functional materials), identifying for each of them a research agenda goal. It is concluded that among these goals are the development of structured materials qualification test-beds and materials acceleration platforms (MAPs) for materials that operate under harsh conditions. Another goal is the development of multi-parameter-based approaches for materials health monitoring based on different non-destructive examination and testing (NDE&T) techniques. Hybrid models that suitably combine physics-based and data-driven approaches for materials behaviour prediction can valuably support these developments, together with the creation and population of a centralised, “smart” database for nuclear materials.

The future development of offshore wind power will include many wind farms built in the same areas. It is known that wind farms produce long distance wakes, which means that we will see more occasions of farm to farm interaction, namely one wind farm operating in the wake of another wind farm. This study investigates how to perform accurate power predictions on large wind farms and how to assess the long distance wakes generated by these farms. The focus of this paper is the production's and wake's sensitivity to the extension of the grid as well as the turbulence when using Large-eddy simulations (LES) with pregenerated Mann turbulence. The aim is to determine an optimal grid which minimizes blockage effects and ensures constant resolution in the entire wake region at the lowest computational cost. The simulations are first performed in the absence of wind turbines in order to assess how the atmospheric turbulence and wind profile are evolving downstream (up to 12,000 m behind the position where the turbulence is imposed). In the second step, 10 turbines are added in the domain (using an actuator disc method) and their production is analyzed alongside the mean velocities in the domain. The blockage effects are tested using grids with different vertical extents. An equidistant region is used in order to ensure high resolution in the wake region. The importance of covering the entire wake structure inside the equidistant region is analyzed by decreasing the size of this region. In this step, the importance of the lateral size of the Mann turbulence box is also analyzed. In the results it can be seen that the flow is acceptably preserved through the empty domain if a larger turbulence box is used. The relative production is increased (due to blockage effects) for the last turbines using a smaller vertical domain, increased for a lower or narrower equidistant region (due to the smearing of the wake in the stretched area) and decreased when using a smaller turbulence box (due to decreased inmixing) The long distance wake behind the row is most impacted by the use of a smaller turbulence box, while the other simulation setups have less influence on these results. In summary, the results show the importance of having relatively large extensions of the domain, large extensions of the equidistant region and especially large extensions of the turbulence box.

The wake recovery behind the Horns Rev wind farm is analysed to investigate the applicability of Large Eddy Simulations (LES) in combination with an actuator disc method (ACD) for farm to farm interaction studies. Periodic boundary conditions on the lateral boundaries are used to model the wind farm (as infinitely wide), using only two columns of turbines. The meteorological conditions of the site are taken into account by introducing wind shear and pre-generated synthetic turbulence to the simulation domain using body forces. Simulations are carried out to study the power production and the velocity deficit in the farm wake. The results are compared to the actual power production as well as to wind measurements at 2 km and 6 km behind the wind farm. The simulated power production inside the farm shows an overall good correlation with the real production, but is slightly overpredicted in the most downstream rows. The simulations overpredict the wake recovery, namely the wind velocity, at long distances behind the farm. Further studies are needed before the presented method can be applied for the simulation of long distance wakes. Suggested parameters to be studied are the development of the turbulence downstream in the domain and the impact of the grid resolution.