Fission Gas

Fission gas release (FGR) from nuclear fuel is a critical factor influencing reactor safety and performance, with research focused on accurately predicting its behavior. Current efforts utilize advanced computational methods, including deep learning architectures like convolutional neural networks (CNNs) with attention mechanisms, to model FGR from fuel microstructure images and improve the accuracy of predictions. This involves developing robust image segmentation techniques to quantify fission gas bubble characteristics, particularly in advanced fuel designs like U-10Zr. Improved understanding of FGR through these modeling approaches is essential for optimizing fuel design and ensuring safe reactor operation.