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ABSTRACT: Until now, the genetic evaluation of the Italian Mediterranean Buffalo has been mainly focused on production traits. However, female fertility affects the efficiency of the dairy industry as it is essential to maintain the profitability of dairy farms. Indeed, the estimation of its genetic component is crucial for its improvement. In this study, 3 measures of buffalo's fertility were analyzed: the age at first calving (AFC), the interval between first and second calving (CIV1), and the interval between second and successive calvings (CIV2_12). Milk yield at 270 d (MY270) was used as a correlated trait. First, genetic parameters were estimated using 7,915 buffalo cows with first calving from 1991 to 2018, then breeding values were calculated from 236,087 buffalo cows. Genetic parameters were estimated by Bayesian inference fitting a multiple-trait animal model using the GIBBS1F90 program, and BLUPF90 was used for estimation of breeding value. The heritability and repeatability estimates of fertility traits were low. The genetic correlations among fertility traits ranged from 0.10 (AFC-CIV1) to 0.92 (CIV1-CIV2_12). Genetic correlation between MY270 and fertility traits was unfavorable, ranging from 0.23 to 0.48. The results from this study can be used as a basis for the future genetic improvement of fertility traits in the Italian Mediterranean Buffaloes.

In fast reactors, restructuring of the fuel micro-structure driven by high temperature and high temperature gradient can cause the formation of columnar grains. The non-spheroidal shape and the non-uniform temperature field in such columnar grains implies that standard models for fission gas diffusion can not be applied. To tackle this issue, we present a reduced order model for the fission gas diffusion process which is applicable in different geometries and with non-uniform temperature fields, maintaining a computational requirement in line with its application in fuel performance codes. This innovative application of reduced order models as meso-scale tools within fuel performance codes represents a first-of-a-kind achievement that can be extended beyond fission gas behaviour.

Helium production in the nuclear fuel matrix during irradiation plays a critical role in the design and performance of Gen-IV reactor fuel, as it represents a life-limiting factor for the operation of fuel pins. In this work, a surrogate model for the helium production rate in fast reactor MOX fuels is developed, targeting its inclusion in engineering tools such as fuel performance codes. This surrogate model is based on synthetic datasets obtained via the SCIANTIX burnup module. Such datasets are generated using Latin hypercube sampling to cover the range of input parameters (e.g., fuel initial composition, fission rate density, and irradiation time) and exploiting the low computation requirement of the burnup module itself. The surrogate model is verified against the SCIANTIX burnup module results for helium production with satisfactory performance.

The behaviour of the fission gas plays an important role in the fuel rod performance. In a previous work, we presented a physics-based model describing intra- and inter-granular behaviour of radioactive fission gas. The model was implemented in SCIANTIX, a mesoscale module for fission gas behaviour, and assessed against the CONTACT 1 irradiation experiment. In this work, we present the multi-scale coupling between the TRANSURANUS fuel performance code and SCIANTIX, used as mechanistic module for stable and radioactive fission gas behaviour. We exploit the coupled code version to reproduce two integral irradiation experiments involving standard fuel rod segments in steady-state operation (CONTACT 1) and during successive power transients (HATAC C2). The simulation results demonstrate the predictive capabilities of the code coupling and contribute to the integral validation of the models implemented in SCIANTIX.

When assessing the radiological consequences of postulated accident scenarios, it is of primary interest to determine the amount of radioactive fission gas accumulated in the fuel rod free volume. The state-of-the-art semi-empirical approach (ANS 5.4–2010) is reviewed and compared with a mechanistic approach to evaluate the release of radioactive fission gases. At the intra-granular level, the diffusion-decay equation is handled by a spectral diffusion algorithm. At the inter-granular level, a mechanistic description of the grain boundary is considered: bubble growth and coalescence are treated as interrelated phenomena, resulting in the grain-boundary venting as the onset for the release from the fuel pellets. The outcome is a kinetic description of the release of radioactive fission gases, of interest when assessing normal and off-normal conditions. We implement the model in SCIANTIX and reproduce the release of short-lived fission gases, during the CONTACT 1 experiments. The results show a satisfactory agreement with the measurement and with the state-of-the-art methodology, demonstrating the model soundness. A second work will follow, providing integral fuel rod analysis by coupling the code SCIANTIX with the thermo-mechanical code TRANSURANUS.

In this work, we propose a new mechanistic model for the treatment of helium behaviour at the grain boundaries in oxide nuclear fuel. The model provides a rate-theory description of helium inter-granular behaviour, considering diffusion towards grain edges, trapping in lenticular bubbles, and thermal re-solution. It is paired with a rate-theory description of helium intra-granular behaviour that includes diffusion towards grain boundaries, trapping in spherical bubbles, and thermal re-solution. The proposed model has been implemented in the meso-scale software designed for coupling with fuel performance codes SCIANTIX. It is validated against thermal desorption experiments performed on doped UO2 samples annealed at different temperatures. The overall agreement of the new model with the experimental data is improved, both in terms of integral helium release and of the helium release rate. By considering the contribution of helium at the grain boundaries in the new model, it is possible to represent the kinetics of helium release rate at high temperature. Given the uncertainties involved in the initial conditions for the inter-granular part of the model and the uncertainties associated to some model parameters for which limited lower-length scale information is available, such as the helium diffusivity at the grain boundaries, the results are complemented by a dedicated uncertainty analysis. This assessment demonstrates that the initial conditions, chosen in a reasonable range, have limited impact on the results, and confirms that it is possible to achieve satisfying results using sound values for the uncertain physical parameters.

Recent developments on spectral diffusion algorithms, i.e., algorithms which exploit the projection of the solution on the eigenfunctions of the Laplacian operator, demonstrated their effective applicability in fast transient conditions. Nevertheless, the numerical error introduced by these algorithms, together with the uncertainties associated with model parameters, may impact the reliability of the predictions on short-lived volatile fission product release from nuclear fuel. In this work, we provide an upper bound on the numerical error introduced by the presented spectral diffusion algorithm, in both constant and time-varying conditions, depending on the number of modes and on the time discretization. The definition of this upper bound allows introducing a methodology to a priori bound the numerical error on short-lived volatile fission product retention.