Review of available models and progress on the sub-models dealing with the intra- and intergranular inert gas behaviour

Current modelling of inert gas behaviour (IGB) in fuel performance codes (FPCs) is mainly correlation‐ based and tailored to light water reactors conditions and for uranium dioxide. Task 6.1 of INSPYRE aims at overcoming these limitations by developing physics‐based mesoscale IGB models allowing fuel performance codes to effectively simulate the IGB in mixed oxide fuels in fast reactor conditions. Physics‐based models are developed to progressively replace purely empirical correlations. These models allow the implementation of a multiscale approach, in which model parameters derived from lower length scale calculations or measurements (arising from other WPs and open literature) are used by mesoscale models. Final step in the multiscale approach is the inclusion of mesoscale models in FPCs, which is the target of Task 7.1 of INSPYRE. In this deliverable, we present the progress achieved towards IGB modelling for FR MOX during the first year of the INSPYRE project. The models considered are either developed specifically for MOX fuels or are developed for other fuel materials but extendable to MOX fuels. Models are categorized among those describing intra‐granular and inter‐granular IGB, as well as the particular IGB in the high burn‐up structure and in restructured grains. The inert gases considered are xenon, krypton and helium, the last one playing a significant role in MOX fuels compared to UO2. We then present the progress made with respect to state‐of‐the‐art models available in FPCs. The focus is on helium production, diffusivity and solubility; on the modelling approach used to describe the formation of high burn‐up structure and on the modelling approach adopted for the treatment of diffusion in restructured grains. Finally, we outline the future model developments envisaged and we clarify the verification and validation strategy, as well as the uncertainty and sensitivity analyses, planned to assess the developed models prior to their integration in fuel performance codes.