Reduced-order model for inertial locomotion of a slender swimmer

Raksha Mahalinkam, Felicity Gong, and Aditya S. Khair
Phys. Rev. E 97, 043102 – Published 3 April 2018

Abstract

The inertial locomotion of an elongated model swimmer in a Newtonian fluid is quantified, wherein self-propulsion is achieved via steady tangential surface treadmilling. The swimmer has a length 2l and a circular cross section of longitudinal profile aR(z), where a is the characteristic width of the cross section, R(z) is a dimensionless shape function, and z is a dimensionless coordinate, normalized by l, along the centerline of the body. It is assumed that the swimmer is slender, ε=a/l1. Hence, we utilize slender-body theory to analyze the Navier-Stokes equations that describe the flow around the swimmer. Therefrom, we compute an asymptotic approximation to the swimming speed, U, as U/us=1β[V(Re)1211zlnR(z)dz]/ln(1/ε)+O[1/ln2(1/ε)], where us is the characteristic speed of the surface treadmilling, Re is the Reynolds number based on the body length, and β is a dimensionless parameter that differentiates between “pusher” (propelled from the rear, β<0) and “puller” (propelled from the front, β>0) -type swimmers. The function V(Re) increases monotonically with increasing Re; hence, fluid inertia causes an increase (decrease) in the swimming speed of a pusher (puller). Next, we demonstrate that the power expenditure of the swimmer increases monotonically with increasing Re. Further, the power expenditures of a puller and pusher with the same value of |β| are equal. Therefore, pushers are superior in inertial locomotion as compared to pullers, in that they achieve a faster swimming speed for the same power expended. Finally, it is demonstrated that the flow structure predicted from our reduced-order model is consistent with that from direct numerical simulation of swimmers at intermediate Re.

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  • Received 22 January 2018

DOI:https://doi.org/10.1103/PhysRevE.97.043102

©2018 American Physical Society

Physics Subject Headings (PhySH)

Fluid Dynamics

Authors & Affiliations

Raksha Mahalinkam, Felicity Gong, and Aditya S. Khair*

  • Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA

  • *akhair@andrew.cmu.edu

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Issue

Vol. 97, Iss. 4 — April 2018

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