| About this Abstract |
| Meeting |
Materials in Nuclear Energy Systems (MiNES) 2021
|
| Symposium
|
Materials in Nuclear Energy Systems (MiNES) 2021
|
| Presentation Title |
3D-reconstruction via Genetic Algorithms: Application to Metallic Fuel |
| Author(s) |
Riccardo Genoni, Davide Pizzocri, Federico Antonello, Tommaso Barani, Lelio Luzzi, Fabiola Cappia |
| On-Site Speaker (Planned) |
Fabiola Cappia |
| Abstract Scope |
Advanced microscopy for nuclear fuels has increased over the last years supporting the understanding of nuclear material irradiation effects. Focused ion beam/scanning electron microscopy (FIB-SEM) serial reconstruction or X-ray tomography are used to determine three-dimensional (3D) microstructure features. These techniques provide fundamental 3D information, but they present some limitations in applications to nuclear fuels, as both techniques can investigate only small amount of material.
A cost-effective approach is the reconstruction of the 3D multi-phase material from two-dimensional images. Such approach, despite intrinsically ill-posed, is of great value and applied in many fields.
Here we study the fission gas bubbles of irradiated metallic fuels with a combination of image analysis and an optimization technique based on genetic algorithm (GA). The aim is to provide quantitative information regarding the porosity in 3D in U-Pu-Zr fuel with minor actinides and to obtain a correlation between the 3D properties and the measurable 2D quantities. |
| Proceedings Inclusion? |
Undecided |