Regime identification for stratified wakes from limited measurements: A library-based sparse regression formulation

Abstract

All objects moving through the atmosphere or the ocean leave behind a fluid dynamic footprint known as a wake. The patterns in this wake are often long-lasting and, moreover, they can contain information about the object that created the wake, e.g., size and speed. In this study, we develop a framework that can identify such information (the ``regime'') based on limited measurements in the wake. Tests using data from simulations as well as laboratory experiments show that this approach holds promise in the development of automated data-driven fluid pattern classifiers.