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A Forced Damped Oscillation Framework for Undulatory Swimming Provides New Insights into How Propulsion Arises in Active and Passive Swimming

Overview of attention for article published in PLoS Computational Biology, June 2013
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Title
A Forced Damped Oscillation Framework for Undulatory Swimming Provides New Insights into How Propulsion Arises in Active and Passive Swimming
Published in
PLoS Computational Biology, June 2013
DOI 10.1371/journal.pcbi.1003097
Pubmed ID
Authors

Amneet Pal Singh Bhalla, Boyce E. Griffith, Neelesh A. Patankar

Abstract

A fundamental issue in locomotion is to understand how muscle forcing produces apparently complex deformation kinematics leading to movement of animals like undulatory swimmers. The question of whether complicated muscle forcing is required to create the observed deformation kinematics is central to the understanding of how animals control movement. In this work, a forced damped oscillation framework is applied to a chain-link model for undulatory swimming to understand how forcing leads to deformation and movement. A unified understanding of swimming, caused by muscle contractions ("active" swimming) or by forces imparted by the surrounding fluid ("passive" swimming), is obtained. We show that the forcing triggers the first few deformation modes of the body, which in turn cause the translational motion. We show that relatively simple forcing patterns can trigger seemingly complex deformation kinematics that lead to movement. For given muscle activation, the forcing frequency relative to the natural frequency of the damped oscillator is important for the emergent deformation characteristics of the body. The proposed approach also leads to a qualitative understanding of optimal deformation kinematics for fast swimming. These results, based on a chain-link model of swimming, are confirmed by fully resolved computational fluid dynamics (CFD) simulations. Prior results from the literature on the optimal value of stiffness for maximum speed are explained.

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Geographical breakdown

Country Count As %
United States 3 4%
Unknown 64 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 24%
Researcher 9 13%
Student > Master 8 12%
Student > Bachelor 7 10%
Other 5 7%
Other 15 22%
Unknown 7 10%
Readers by discipline Count As %
Engineering 23 34%
Agricultural and Biological Sciences 7 10%
Mathematics 6 9%
Sports and Recreations 6 9%
Physics and Astronomy 4 6%
Other 8 12%
Unknown 13 19%