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Using computational and mechanical models to study animal locomotion

Cornell Affiliated Author(s)

Author

L.A. Miller
D.I. Goldman
T.L. Hedrick
E.D. Tytell
Z.J. Wang
J. Yen
S. Alben

Abstract

Recent advances in computational methods have made realistic large-scale simulations of animal locomotion possible. This has resulted in numerous mathematical and computational studies of animal movement through fluids and over substrates with the purpose of better understanding organisms' performance and improving the design of vehicles moving through air and water and on land. This work has also motivated the development of improved numerical methods and modeling techniques for animal locomotion that is characterized by the interactions of fluids, substrates, and structures. Despite the large body of recent work in this area, the application of mathematical and numerical methods to improve our understanding of organisms in the context of their environment and physiology has remained relatively unexplored. Nature has evolved a wide variety of fascinating mechanisms of locomotion that exploit the properties of complex materials and fluids, but only recently are the mathematical, computational, and robotic tools available to rigorously compare the relative advantages and disadvantages of different methods of locomotion in variable environments. Similarly, advances in computational physiology have only recently allowed investigators to explore how changes at the molecular, cellular, and tissue levels might lead to changes in performance at the organismal level. In this article, we highlight recent examples of how computational, mathematical, and experimental tools can be combined to ultimately answer the questions posed in one of the grand challenges in organismal biology: "Integrating living and physical systems." © 2012 The Author. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved.

Date Published

Journal

Integrative and Comparative Biology

Volume

52

Issue

5

Number of Pages

553-575,

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867781035&doi=10.1093%2ficb%2fics115&partnerID=40&md5=ac2f4f8538b47399c38d2c0cd397af3e

DOI

10.1093/icb/ics115

Research Area

Group (Lab)

Z. Jane Wang Group

Funding Source

1022619
1022802
FRG 0854961
OCE-0928491
1132986
CRCNS R01 NS054271
FA9550-10-1-006
111 234
IOS-0920358

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