High-resolution particle-based 3D velocimetry using divergence-free radial basis functions
ORAL
Abstract
We present a new method of inferring high-resolution 3D divergence-free velocity fields from particle image tomograms. This method – termed tomographic particle flow velocimetry (T-PFV) – is based on representing the velocity field as a linear combination of divergence-free radial basis functions; the piece-wise constant representation of the estimated velocity field that is inherent to tomographic particle image velocimetry (T-PIV) is replaced by a smooth representation that automatically satisfies conservation of mass. The appropriate linear combination is determined using a non-regularized optical flow framework. We provide a detailed evaluation of T-PFV in terms of accuracy, spatial resolution, and sensitivity to parameters based on 3D constant-density DNS data. We also show that T-PFV yields substantial improvements in accuracy and spatial resolution compared to T-PIV over a wide range of parameters.
*This work was supported by the US Air Force Office of Scientific Research under Grant FA9550-17, Project Monitor Dr. Chiping Li, and the Natural Science and Engineering Research Council of Canada (NSERC) through an Alexander Graham Bell Canada Graduate Scholarship.
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Presenters
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Keishi Kumashiro
- University of Toronto Institute for Aerospace Studies