Cross-Correlation Analysis of Digital Speckle Photography View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09

AUTHORS

N. B. Bazylev, N. A. Fomina

ABSTRACT

This paper describes new algorithms for processing noisy specklograms, which permit quantitative diagnostics of the microstructure of shock-wave flows with a subpicosecond accuracy with the use of statistical analysis of numerically registered speckle fields disturbed by the refraction in the investigated flows. The software developed by us permits reconstructing up to 10,000 vector angles of probe radiation deflection in a two-dimensional region of size 20 × 30 mm2 in imaging a speckle field with optical magnification M = 1. More... »

PAGES

1241-1249

References to SciGraph publications

  • 2008-03. Measurements of admixture concentration fluctuations in a turbulent shear flow using an averaged Talbot image in EXPERIMENTS IN FLUIDS
  • 1996-11. A method of tracking ensembles of particle images in EXPERIMENTS IN FLUIDS
  • 2000-05. On the applicability of background oriented optical tomography for large scale aerodynamic investigations in EXPERIMENTS IN FLUIDS
  • 1996-04. Visualization of turbulence anisotropy by single exposure speckle photography in EXPERIMENTS IN FLUIDS
  • 2018-07. New Schemes of Digital Speckle Photography in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2008-01. Measurement of concentration pulsations in a shear turbulent flow by the method of averaged Talbot images in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2010-03. Characteristics of erosion plasma in the region of interaction of a flow with an obstacle in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2012-01. Dynamics of interaction of erosion plasma counterflows in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2009. Quantitative diagnostics of shock wave - boundary layer interaction by digital speckle photography in SHOCK WAVES
  • 2006-12. Tomographic particle image velocimetry in EXPERIMENTS IN FLUIDS
  • 2013-07. Laser speckle technology in stomatology. diagnostics of stresses and strains of hard biotissues and orthodontic and orthopedic structures in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2012-07. Increase in the rate of fuel combustion on addition of nanosized carbon particles in JOURNAL OF ENGINEERING PHYSICS AND THERMOPHYSICS
  • 2000-01. A comparative study of the MQD method and several correlation-based PIV evaluation algorithms in EXPERIMENTS IN FLUIDS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10891-018-1854-4

    DOI

    http://dx.doi.org/10.1007/s10891-018-1854-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107608985


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