Search Results for author: Beverley J. McKeon

Found 2 papers, 1 papers with code

The transformative potential of machine learning for experiments in fluid mechanics

no code implementations28 Mar 2023 Ricardo Vinuesa, Steven L. Brunton, Beverley J. McKeon

The field of machine learning has rapidly advanced the state of the art in many fields of science and engineering, including experimental fluid dynamics, which is one of the original big-data disciplines.

Experimental Design

Modal Analysis of Fluid Flows: An Overview

3 code implementations5 Feb 2017 Kunihiko Taira, Steven L. Brunton, Scott T. M. Dawson, Clarence W. Rowley, Tim Colonius, Beverley J. McKeon, Oliver T. Schmidt, Stanislav Gordeyev, Vassilios Theofilis, Lawrence S. Ukeiley

Simple aerodynamic configurations under even modest conditions can exhibit complex flows with a wide range of temporal and spatial features.

Fluid Dynamics

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