Abstract
The description of intra-granular fission gas behaviour is a fundamental part of any model for the prediction of fission gas release and swelling in nuclear fuel. In this work we present a model describing the evolution of intra-granular fission gas bubbles in terms of bubble number density and average size, coupled to gas release to grain boundaries. The model considers the fundamental processes of single gas atom diffusion, gas bubble nucleation, re-solution and gas atom trapping at bubbles. The model is derived from a detailed cluster dynamics formulation, yet it consists of only three differential equations in its final form; hence, it can be efficiently applied in engineering fuel performance codes while retaining a physical basis. We discuss improvements relative to previous single-size models for intra-granular bubble evolution. We validate the model against experimental data, both in terms of bubble number density and average bubble radius. Lastly, we perform an uncertainty and sensitivity analysis by propagating the uncertainties in the parameters to model results.
Highlights
Given the fundamental role played by fission gas swelling and release in the thermo-mechanical behaviour of nuclear fuel rods during irradiation [1,2], models of fission gas behaviour (FGB) must be included in fuel performance codes
We developed a model for the description of the intra-granular behaviour of fission gas in oxide fuel
The model computes the evolution of intra-granular bubble number density and size coupled to intra-granular gas atom diffusion to grain boundaries
Summary
Given the fundamental role played by fission gas swelling and release in the thermo-mechanical behaviour of nuclear fuel rods during irradiation [1,2], models of fission gas behaviour (FGB) must be included in fuel performance codes. The traditional approach adopted in engineering-scale fuel performance codes describes the evolution of intra-granular fission gas bubbles by relying on empirical correlations. These correlations estimate the mean bubble size and number density as a function of macroscopic parameters, e.g. the local temperature [6,14]. Cluster dynamics models calculate the entire bubble (atom cluster) size distribution and the distribution evolution over time by solving coupled rate equations for the number densities of clusters of different sizes These advanced modelling approaches are computationally intensive and cannot be used directly for fuel performance code applications [4].
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