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.

A model that describes creep behavior is essential in the design or life assessment of components and systems that operate at high temperatures. Using the RCC-MRx data and the LCSP (logistic creep strain prediction) model, processed design data were generated over the whole creep regime of 316L(N) steel—i.e., primary, secondary, and tertiary creep. The processed design data were used to develop three models with different approaches for the creep rate: a phenomenological approach; an artificial neural network; and an artificial intelligence method based on symbolic regression and genetic programming. It was shown that all three models are capable of describing the true creep rate as a function of true creep strain and true stress over a wide range of engineering stresses and temperatures without the need of additional micro-structural information. Furthermore, the results of finite element simulations reproduce the trends of experimental data from the literature.

This paper presents a finite element analysis of the small punch creep test for 316L(N), which is compared with experimental data for 650 and 700 °C. Special emphasis is placed on (i) assessing the influence of friction and (ii) comparing two different creep models: the simple Norton creep and the more general creep model. The computed normalized deflection rate versus time is almost identical for all cases, which allows for scaling of the results. The computed time to rupture increases linearly with the friction coefficient due to a reduction in the mean stress. There is a good overall agreement between the experimental values and the computed deflection rate for a friction coefficient of around 0.3. It is shown that the initial reduction in deflection rate is due to stress relaxation and homogenization, and is only marginally affected by primary creep hardening. The computed results are compared with the equivalent stress and strain rates in the recently published small punch standard (EN 10371). The computed von Mises stresses at minimum deflection decrease linearly with the friction coefficient but are consistently slightly higher than the equivalent stress in the standard. For the strain rates, the computed values are significantly higher than the equivalent values in the standard. The presented simulations give a deeper insight of the small punch creep and impact of key parameters such the friction coefficient and in general as a guidance to refinement and improvement of the empirically based formulae in the standard.