journal article·2023-04Open access

Oriented intra-granular bubble transport due to coupling of pinned bubble growth and dislocation climb

L. Noirot, L. Verma, P. Maugis

Abstract

The intra-granular fission gas release during post-irradiation annealing tests cannot be predicted if bubble motion is not taken into account. Indeed, without irradiation, the equilibrium between trapping and re-solution is completely shifted in favor of trapping, the dynamic resolution due to fission spikes no longer existing. Moreover, the sink strength of the population of intragranular bubbles is greater by a factor ∼ 1000 than the sink strength of the grain surface. Trapped in supposedly immobile bubbles, the gas would not escape from the grain, which is in contradiction with experimental observations. Several alternative scenarios involving bubble movement emerged to explain the observed fission gas release. The purpose of our work is to assess these scenarios using simulation. In a previous article, it was demonstrated that neither the movement of bubbles in a vacancy gradient, nor the Brownian movement of bubbles, nor the combination of them, could explain the large fission gas release obtained during post-irradiation annealing in our reference experiment. This demonstration was performed using a mesoscale model, called BEEP, where individual bubbles are described, along with the diffusion of vacancies from each bubble to the other, as well as from the free surface. In this paper, we extend the BEEP model to assess the role of dislocations in interaction with highly pressurized bubbles. It is concluded that a mechanism of dislocation climb coupled with the growth of highly pressurized pinned bubbles may explain the large intra-granular fission gas release in annealing conditions.
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Nuclear Materials and Properties · Radioactive element chemistry and processing · Nuclear Physics and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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