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Issue 11, 2017

Tracking particles with large displacements using energy minimization

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Abstract

We describe a method to track particles undergoing large displacements. Starting with a list of particle positions sampled at different time points, we assign particle identities by minimizing the sum across all particles of the trace of the square of the strain tensor. This method of tracking corresponds to minimizing the stored energy in an elastic solid or the dissipated energy in a viscous fluid. Our energy-minimizing approach extends the advantages of particle tracking to situations where particle imaging velocimetry and digital imaging correlation are typically required. This approach is much more reliable than the standard squared-displacement minimizing approach for spatially-correlated displacements that are larger than the typical interparticle spacing. Thus, it is suitable for particles embedded in a material undergoing large deformations. On the other hand, squared-displacement minimization is more effective for particles undergoing uncorrelated random motion. In the ESI, we include a flexible MATLAB particle tracker that implements either approach with a robust optimal assignment algorithm. This implementation returns an estimation of the strain tensor for each particle, in addition to its identification.

Graphical abstract: Tracking particles with large displacements using energy minimization

Supplementary files

Article information


Submitted
01 Sep 2016
Accepted
22 Feb 2017
First published
22 Feb 2017

Soft Matter, 2017,13, 2201-2206
Article type
Paper

Tracking particles with large displacements using energy minimization

R. Boltyanskiy, J. W. Merrill and E. R. Dufresne, Soft Matter, 2017, 13, 2201 DOI: 10.1039/C6SM02011A

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