Year: 2014
Type: preprint
Abstract: Prediction is a fundamental objective of science. It is more difficult for chaotic and complex systems like turbulence. Here we use information theory to quantify spatial prediction using experimental data from a turbulent soap film. At high Reynolds number $Re$ where a cascade exists, turbulence is becoming easier to predict as the inertial range broadens. A transition corresponding to the emergence of a cascade at low $Re$ is detected by looking at turbulence through prediction.
Source: arXiv (Cornell University)
Authors: Cerbus, Rory, Goldburg, Walter
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2297085040