A sparse optical flow inspired method for 3D velocimetry

We introduce a three-dimensional three-component particle-based velocimetry method that expands the methodology of optical flow to three dimensions. The proposed scheme, sparse particle flow velocimetry (SPFV), uses a sparse representation of intensity fields with kernel functions to facilitate effi...

Full description

Saved in:
Bibliographic Details
Published inExperiments in fluids Vol. 64; no. 4
Main Authors Lu, George, Steinberg, Adam, Yano, Masayuki
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2023
Springer Nature B.V
Subjects
Difference equations
Direct numerical simulation
Displacement
Engineering
Engineering Fluid Dynamics
Engineering Thermodynamics
Fluid- and Aerodynamics
Freezing
Heat and Mass Transfer
Image reconstruction
Isotropic turbulence
Kernel functions
Optical flow (image analysis)
Optimization
Performance evaluation
Reacting flow
Representations
Research Article
Robustness (mathematics)
Spatial resolution
Three dimensional flow
Velocimetry
Online AccessGet full text

Cover

More Information
Summary:We introduce a three-dimensional three-component particle-based velocimetry method that expands the methodology of optical flow to three dimensions. The proposed scheme, sparse particle flow velocimetry (SPFV), uses a sparse representation of intensity fields with kernel functions to facilitate efficient computation in 3D. In addition, to provide robust performance for the large particle displacements seen in images, the sparse representation is combined with a multi-resolution optimization scheme based on an energy functional derived from the displaced frame difference equation; however, this formulation is not reliant on linearized coarse-to-fine warping schemes to enable estimations of large displacements at the cost of potentially freezing large scale velocity features. Performance of SPFV is evaluated in terms of accuracy and spatial resolution, using synthetic particle images from a direct numerical simulation of isotropic turbulence. SPFV yields lower errors than tomographic PIV (T-PIV) and is capable of resolving finer scale features, even for large particle displacements and in the presence of artificial tomographic reconstruction artifacts. The method is also validated on experimental images of reacting flows and shows good agreement with T-PIV results.
ISSN:0723-4864
1432-1114
DOI:10.1007/s00348-023-03593-z