An algorithm to estimate unsteady and quasi-steady pressure fields from velocity field measurements
Dabiri, John O.
Gemmell, Brad J.
Colin, Sean P.
Costello, John H.
MetadataShow full item record
We describe and characterize a method for estimating the pressure field corresponding to velocity field measurements such as those obtained by using particle image velocimetry. The pressure gradient is estimated from a time series of velocity fields for unsteady calculations or from a single velocity field for quasi-steady calculations. The corresponding pressure field is determined based on median polling of several integration paths through the pressure gradient field in order to reduce the effect of measurement errors that accumulate along individual integration paths. Integration paths are restricted to the nodes of the measured velocity field, thereby eliminating the need for measurement interpolation during this step and significantly reducing the computational cost of the algorithm relative to previous approaches. The method is validated by using numerically simulated flow past a stationary, two-dimensional bluff body and a computational model of a three-dimensional, self-propelled anguilliform swimmer to study the effects of spatial and temporal resolution, domain size, signal-to-noise ratio and out-of-plane effects. Particle image velocimetry measurements of a freely swimming jellyfish medusa and a freely swimming lamprey are analyzed using the method to demonstrate the efficacy of the approach when applied to empirical data.
© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Experimental Biology 217 (2014): 331-336, doi:10.1242/jeb.092767.
Suggested CitationJournal of Experimental Biology 217 (2014): 331-336
The following license files are associated with this item:
Showing items related by title, author, creator and subject.
Dawson, Benjamin G.; Heyer, Gail W.; Eppi, Rene E.; Kalmijn, Adrianus J. (Woods Hole Oceanographic Institution, 1981-05)From previous experiments, we learned that sharks, skates and rays have an electric sense that enables them to detect voltage gradients as low as 0.01 µV/cm within the frequency range from DC up to 8 Hz. The animals ...
Gemmell, Brad J.; Fogerson, Stephanie M.; Costello, John H.; Morgan, Jennifer R.; Dabiri, John O.; Colin, Sean P. (Company of Biologists, 2016-12-14)Swimming animals commonly bend their bodies to generate thrust. For undulating animals such as eels and lampreys, their bodies bend in the form of waves that travel from head to tail. These kinematics accelerate the flow ...
Characterization of underwater target geometry from Autonomous Underwater Vehicle sampling of bistatic acoustic scattered fields Fischell, Erin M. (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2015-06)One of the long term goals of Autonomous Underwater Vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using ...