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Related Experiment Videos

PDV-based estimation of ejecta particles' mass-velocity function from shock-loaded tin experiment.

J-E Franzkowiak1, G Prudhomme1, P Mercier1

  • 1CEA, DAM, DIF, F-91297 Arpajon, France.

The Review of Scientific Instruments
|April 2, 2018
PubMed
Summary
This summary is machine-generated.

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Explosive-driven micro-jetting creates a cloud of metallic particles. Researchers used Photonic Doppler Velocimetry (PDV) and piezoelectric sensors to analyze particle properties, validating the PDV method for ejecta characterization.

Area of Science:

  • Materials Science
  • Physics
  • Shock Physics

Background:

  • Dynamic fragmentation of explosively driven surfaces generates high-speed ejecta.
  • Micro-jetting and subsequent jet fragmentation form micron-sized metallic particles.
  • Characterizing the areal mass, velocity, and particle size distribution of these ejecta clouds is crucial.

Purpose of the Study:

  • To present experimental measurements of ejecta cloud mass and velocity.
  • To relate integrated areal mass to Photonic Doppler Velocimetry (PDV) power spectral density.
  • To develop and apply models for PDV spectrogram analysis to estimate ejecta properties.

Main Methods:

  • Explosive driving of a metallic tin plate with defined surface finish.
  • Measurement of areal mass using lithium-niobate-piezoelectric sensors.

Related Experiment Videos

  • Acquisition of time-velocity spectrograms using Photonic Doppler Velocimetry (PDV).
  • Development of two PDV spectrogram analysis models (speckle statistics and average spectrum).

    • Main Results:

    • Experimental mass and velocity data of the ejecta cloud were obtained.
    • A power law particle size distribution was assumed to link areal mass to PDV spectral density.
    • The average spectrum PDV model was used for maximum likelihood estimation of cloud parameters.
    • Estimated integrated areal mass from PDV data showed good agreement with piezoelectric sensor results.

    Conclusions:

    • The study successfully correlated integrated areal mass with PDV power spectral density.
    • PDV data analysis, particularly using the average spectrum model, is effective for estimating ejecta cloud properties.
    • Correlating different diagnostic measurements is vital for retrieving physical properties of ejecta particles.