Engineering study employs deep learning to explain extreme events

At the core of uncovering extreme events such as floods is the physics of fluids – specifically turbulent flows. Researchers leveraged a computer-vision deep learning technique and adapted it for nonlinear analysis of extreme events in wall-bounded turbulent flows, which are pervasive in numerous physics and engineering applications and impact wind and hydrokinetic energy, among others. Results show the technique employed can be invaluable for accurately identifying the sources of extreme events in a completely data-driven manner.