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An information-theoretic approach to study fluid–structure interactions

Published online by Cambridge University Press:  13 June 2018

Peng Zhang
Affiliation:
Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA
Maxwell Rosen
Affiliation:
Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA
Sean D. Peterson
Affiliation:
Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
Maurizio Porfiri*
Affiliation:
Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA
*
Email address for correspondence: mporfiri@nyu.edu

Abstract

The question of causality is pervasive to fluid–structure interactions, where it finds its most alluring instance in the study of fish swimming in coordination. How and why fish align their bodies, synchronize their motion, and position in crystallized formations are yet to be fully understood. Here, we posit a model-free approach to infer causality in fluid–structure interactions through the information-theoretic notion of transfer entropy. Given two dynamical units, transfer entropy quantifies the reduction of uncertainty in predicting the future state of one of them due to additional knowledge about the past of the other. We demonstrate our approach on a system of two tandem airfoils in a uniform flow, where the pitch angle of one airfoil is actively controlled while the other is allowed to passively rotate. Through transfer entropy, we seek to unveil causal relationships between the airfoils from information transfer conducted by the fluid medium.

Type
JFM Papers
Copyright
© 2018 Cambridge University Press 

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