Particle Image Velocimetry

Particle Image Velocimetry (PIV) is a widely used optical technique for measuring fluid velocity fields, primarily aiming to quantify flow patterns and their characteristics. Current research focuses on improving PIV accuracy and efficiency through advanced image processing techniques, including deep learning-based methods like convolutional neural networks and variational autoencoders, as well as novel algorithms such as Graph Optimal Transport and Residual Dynamic Mode Decomposition for enhanced data analysis and flow reconstruction. These advancements are significantly impacting various fields, enabling more accurate characterization of complex flows in applications ranging from engine design and biomedical fluid mechanics to the study of turbulence and active nematics.