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Testing image-velocimetry methods for turbulence diagnostics.

Y W Enters1,2, S Thomas1, M Hill1

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Combining cross-correlation time-delay estimation (CCTDE) and dynamic time warping (DTW) improves image-based velocity inference. This study enhances both techniques for accurate velocimetry, offering practical workflows for experimental data analysis.

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Area of Science:

  • Fluid dynamics
  • Image analysis
  • Plasma physics

Background:

  • Image-based velocimetry is crucial for analyzing dynamic systems.
  • Cross-correlation time-delay estimation (CCTDE) and dynamic time warping (DTW) are established techniques for inferring velocity from image sequences.
  • Understanding the comparative strengths and weaknesses of CCTDE and DTW is essential for optimizing their application.

Purpose of the Study:

  • To investigate and compare the performance of CCTDE and DTW for image-based velocity inference.
  • To identify novel methods for improving the accuracy and precision of both velocimetry techniques.
  • To provide a practical workflow for applying these enhanced techniques to experimental data.

Main Methods:

  • Systematic testing of CCTDE and DTW using synthetic data to analyze accuracy and precision.
  • Evaluation of technique performance under various conditions, including different frame rates, flow velocities, and spatial resolutions.
  • Investigation of robustness against artifacts like the barber pole illusion and performance with sheared flows.

Main Results:

  • CCTDE achieved accurate velocity inference with significantly shorter intervals (1 per 32 frames) compared to literature standards (≥256 frames).
  • DTW demonstrated greater robustness against the barber pole illusion and could infer flow fields from low-resolution data (8x8 spatial channels).
  • A pattern in CCTDE accuracy related to velocity magnitude was identified, and spurious velocities from the barber pole illusion can now be predicted.

Conclusions:

  • The complementary strengths of CCTDE and DTW suggest their combined use for optimal velocimetry.
  • Novel findings significantly enhance the performance and applicability of both techniques.
  • The study provides practical workflows for integrating these improved velocimetry methods into experimental analysis.