Dataset: Lagrangian Structure and Stretching in Bacterial Turbulence Modeling Results from February 2020 (VIC project)

Release Date:2023-12-31Final no updates expectedVersion 1 (2023-09-06)Dataset Type:experimentalDataset Type:model results

Principal Investigator: Jeffrey Guasto (Tufts University)

Scientist, Contact: Richard J. Henshaw (Tufts University)

BCO-DMO Data Manager: Sawyer Newman (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Viral induced chemotaxis mediating cross-trophic microbial interactions and carbon flux (VIC)


Abstract

Dense suspensions of active, self-propelled agents spontaneously exhibt large-scale, chaotic flow structures. Descriptions of their dynamics have predominately focused on characterization of spatiotemporal correlation of the velocity field, but their transport and mixing properties remain largely unknown. In this work, we use Lagrangian analysis techniques to study the chaotic flow field generated by "bacterial turbulence" in dense suspensions of Bacillus subtilis. High-resolution velocity field...

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Velocity Field Variables:

U: u-component of the velocity fields

V: v-component of the velocity fields

X,Y: XY coordinates produced from the PIV analysis (meshgrid layout)

 

Stretching Field Variables:

TINT: Integration time for tracer particles (s)

choice: parameter choices for numerical experiment, see code for details

stretch: a Nx1 cell of the stretching field for this particular integration time, where each cell is a frame

tintegrate: time vector of the tracer particle integration

x_field, y_field: Initial xy coordinates of tracer particle grids. Formed using meshgrid


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Results

R.J. Henshaw and J.S. Guasto. Lagrangian structure and stretching of bacterial turbulence. In preparation
Methods

Parsa, S., Guasto, J. S., Kishore, M., Ouellette, N. T., Gollub, J. P., & Voth, G. A. (2011). Rotation and alignment of rods in two-dimensional chaotic flow. Physics of Fluids, 23(4). https://doi.org/10.1063/1.3570526