Abstract

The nuclear reactors themselves are complex systems whose responses are driven by interactions between different physics phenomena within the reactor core. Traditionally, the different physics phenomena have been analyzed separately and its interaction considered via boundary conditions or closure models. However, in parallel with the development of computational technology, multi-physics coupled simulations are being used to obtain accurate predictions thanks to the consideration of the feedback effects on the fly (on-line). In the nuclear systems the fuel temperature is an important feedback parameter used to obtain the nuclear cross sections at given conditions by the neutron kinetics codes. An accurate prediction of temperature profile within the fuel rod involve several physics such as neutron kinetics, mechanics, material behavior and properties, heat transfer, thermal-hydraulics, and even chemistry. The pellet to clad gap conductance is possibly the most important source of uncertainty in the solution of conductivity equation in the fuel rod and the fuel temperature prediction. The gap conductance depends on two effects: the pellet to gap distance and the conductivity of the gas species that fill the gap. In this research work, the authors are focused on improving of the prediction of the gap gas conductivity in CTFFuel by implementing a fission gas release model in the code. The objective of this contribution is the implementation of a transient fission gas release model in CTFFuel and its validation using the experimental data available in the OECD/NEA International Fuel Performance Experiments (IFPE) database. CTFFuel is an isolated fuel heat transfer capability within the framework of CTF code, the state-of-the-art version of the Coolant Boiling in Rod Arrays Code – Two-Fluid (COBRA-TF) sub-channel thermal-hydraulic code. The code is being jointly developed by North Carolina State University (NCSU) and Oak Ridge National Laboratory (ORNL) within the US Department of Energy (DOE) Consortium for Advanced Simulation of LWRs (CASL).

Highlights

  • An optimal fuel solver has to be designed to provide fuel temperature feedback with sufficient accuracy and low computational cost

  • A mechanistic Fission Gas Release (FGR) model based on the UO2 grain size, the concentration of fission gas in the grain boundaries and the diffusion of the fission gases throughout the fuel pellet has been implemented in CTFFuel

  • A new mechanistic FGR model has been implemented in CTFFuel to predict the amount of fission gas isotopes released to the gap with the objective of improve the accuracy of the gap conductance predictions

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Summary

INTRODUCTION

An optimal fuel solver has to be designed to provide fuel temperature feedback with sufficient accuracy and low computational cost. This provides benefits such as the easy development and code-to-code verification or standalone fuel behavior uncertainty quantification. The amount of fission gas released and impact of this model on the temperature prediction have been analyzed by the comparison with available experimental data summarized in the OECD/NEA International Fuel Performance Experiments (IFPE) database. With the final goal of improving the gap conductance prediction, the amount of fission gas computed by the model is used to update the value of the gap gas pressure and the conductivity of the mix of gas species that fill the gap.

FISSION GAS RELEASE MODEL
Implemented mechanistic fission gas release model
Details of the model implementation
Fission gas production
Grain growth model
High Burnup Rim Thickness
Gas diffusion constant
Fission gas release model
RESULTS AND DISCUSSION
CONCLUSIONS
Full Text
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