Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published December 7, 2017 | Published
Journal Article Open

A pressure-based force and torque prediction technique for the study of fish-like swimming


Many outstanding questions about the evolution and function of fish morphology are linked to swimming dynamics, and a detailed knowledge of time-varying forces and torques along the animal's body is a key component in answering many of these questions. Yet, quantifying these forces and torques experimentally represents a major challenge that to date prevents a full understanding of fish-like swimming. Here, we develop a method for obtaining these force and torque data non-invasively using standard 2D digital particle image velocimetry in conjunction with a pressure field algorithm. We use a mechanical flapping foil apparatus to model fish-like swimming and measure forces and torques directly with a load cell, and compare these measured values to those estimated simultaneously using our pressure-based approach. We demonstrate that, when out-of-plane flows are relatively small compared to the planar flow, and when pressure effects sufficiently dominate shear effects, this technique is able to accurately reproduce the shape, magnitude, and timing of locomotor forces and torques experienced by a fish-like swimmer. We conclude by exploring of the limits of this approach and its feasibility in the study of freely-swimming fishes.

Additional Information

© 2017 Lucas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This work was supported by a National Science Foundation Graduate Research Fellowship under grant DGE-1144152 and a Harvard University Chapman Fellowship to KNL and by the Office of Naval Research Multi-University Research Initiative Grant N000141410533 monitored by Dr. Bob Brizzolara to GVL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Thanks to Francis Carr, Ryan Feather, Patrick Thornycroft, Brad Gemmell, and Eric Tytell for technical assistance, and to Iman Borazjani, Kara Feilich, Elena Kramer, and Pete Girguis for helpful discussions. We also thank Eric Tytell, Sean Colin, and the anonymous reviewers for their feedback on earlier versions of this manuscript. The authors declare that no competing interests exist. Data Availability: All video and force-torque sensor data files are available from the "Video and sensor data for pressure-based force calculation validation" database on Harvard Dataverse available at http://dx.doi.org/10.7910/DVN/5NCA5X. The Dabiri et al. (2014, J. Exp. Biol.) pressure-field algorithm is freely available at http://dabirilab.com/software/ as executable software in a .p file format, which will launch as a GUI in Matlab where the user can load velocity data and generate the corresponding pressure fields. Please note that the .p file will not render as a readable code in a text editor, and the reader is highly encouraged to reference the ReadMe document provided with the GUI. The algorithm is also available at https://github.com/kelseynlucas, along with all other scripts used for data processing.

Attached Files

Published - journal.pone.0189225.pdf


Files (29.3 MB)
Name Size Download all
29.3 MB Preview Download

Additional details

September 15, 2023
October 23, 2023