Numerical simulation of hydrogen isotope bubbles evolution and their effect on fuel retention in tungsten

The 2D Hydrogen Isotope Inventory Process code with Monte Carlo bubble growth model (HIIPC2D-MC) has been upgraded by adding surface retention and self-clustering bubble nucleation to study the evolution of hydrogen isotope (HI) bubble and its impact on fuel retention. In this code, fuel retention is simulated by HIIPC2D, while the nucleation and growth of the bubble is modeled by 3D Monte Carlo code. Firstly, the dynamic behavior and mechanism of bubble nucleation is studied via self-clustering nucleation module. The effects of irradiation flux, material temperature (T) and trap concentration on bubble nucleation are systematically studied. The results show that the low T promotes the self-clustering bubble nucleation, large irradiation flux and low trap density lead to high nucleation rate. The long irradiation time facilitates the formation of bubbles via hydrogen self-clustering. Then, the time evolution of nucleation and growth of the bubbles is demonstrated. After the nucleation, both cascade-coalescence and pressure drive the bubbles to grow. The most and largest bubbles appear in the near-surface layer, and the HI inside the bubble plays important role on the total fuel retention. The simulation indicates the behaviors of the bubbles depend strongly on the operation regime in a tokamak. However, the bubble burst (blistering burst in experiment) is not included in the model, which will affect the bubble performance during long term irradiation.

Automated summary

The 2D Hydrogen Isotope Inventory Process code with Monte Carlo bubble growth model (HIIPC2D-MC) has been upgraded to study the evolution of hydrogen isotope (HI) bubble and its impact on fuel retention. The study reveals that low temperature promotes self-clustering bubble nucleation, high irradiation flux and low trap concentration lead to high nucleation rate, and long irradiation time facilitates the formation of bubbles via hydrogen self-clustering.