The cladding of nuclear fuel rods used in Pressurized Water Reactor, made of zirconium alloys, is the first barrier for the confinement of radioactive nuclei. In-reactor, the cladding is subjected to radiation damage resulting in a change of its mechanical properties. After in-reactor use, the fuel rods are transported and stored. During these various steps, the radiation damage is partially annealed, leading to another evolution of the material properties. All these evolutions are still not well understood.
The objective of this PhD work is to better understand the deformation mechanisms and the mechanical behavior of zirconium alloys after irradiation, and after a partial annealing of the radiation damage. This will help to better predict the behavior of the cladding tube after use and thus guaranty the confinement of radioactive nuclei.
In order to achieve this goal, original experimental methods and advanced numerical simulations will be used. Ion irradiations will be conducted in order to reproduce the radiation damage. Heat treatments will then be done on the specimens after irradiation. Small tensile samples will be strained in situ, after annealing, inside a transmission electron microscope, at room temperature or at high temperature. Deformation mechanisms observed at nanometer scale and in real time will be simulated using dislocation dynamics, at the same time and space scales. Large scale dislocation dynamics simulations will then be conducted in order to deduce the single-crystal behavior of the material. In parallel with this study at the nanometric scale, a study will also be conducted at the micrometric scale. Nanoindentation and micropillar compression tests will be performed to assess the mechanical behavior after irradiation and annealing. The results of mechanical tests will be compared with large-scale dislocation dynamics numerical simulations.
This study will allow a better understanding of the special behavior of zirconium alloys after irradiation and annealing and then help to develop physically based predictive models. In a future prospect, this work will contribute to improve the safety during transport and storage of spent nuclear fuel.