A robust and accurate technique for Lagrangian tracking of bubbles and detecting fragmentation and coalescence

Qiang Gao, Grant B. Deane, Han Liu, Lian Shen

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4 Scopus citations

Abstract

A technique for Lagrangian tracking of bubbles and detecting their time-evolution behaviors is presented. Five possible behaviors are considered: formation, extinction, continuity, binary fragmentation, and binary coalescence. The technique is based on establishing a network of mappings between bubbles identified at adjacent time instants. The mappings are determined by selecting the minimum from a set of pseudo-distance errors, which are themselves based on constraints imposed on bubble position, velocity, and volume between adjacent time instants. The technique is validated through numerical inspection of the pseudo-distance errors and visual verification of over 16,000 bubble events identified in a simulated breaking wave. The accuracies for continuity, binary fragmentation, and binary coalescence are estimated to be 99.5%, 90%, and 95%, respectively, when the analysis is limited to bubbles of sizes of at least two grid lengths. The effects of varying pseudo-distance error parameters and time resolution are also investigated. The technique robustly tracks bubbles and the occurrence of binary fragmentation and binary coalescence in a breaking wave when these processes occur away from the complex air–water interface structures and bubbles are of comparable scale. Detecting the fragmentation and coalescence of large-scale and complex air–water interfaces remains an outstanding problem.

Original languageEnglish (US)
Article number103523
JournalInternational Journal of Multiphase Flow
Volume135
DOIs
StatePublished - Feb 1 2021

Bibliographical note

Funding Information:
This research was made possible by a grant from The Gulf of Mexico Research Initiative. The support from the Office of Naval Research, with grants N00014-16-1-2192 and N00014-17-1-2658 to Q.G., H.L., and L.S. and grant N00014-17-1-2633 to G.B.D., are gratefully acknowledged. Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org/data/R5.x273.000:0003 ( doi:10.7266/6JYHYC9W ).

Funding Information:
This research was made possible by a grant from The Gulf of Mexico Research Initiative. The support from the Office of Naval Research, with grants N00014-16-1-2192 and N00014-17-1-2658 to Q.G. H.L. and L.S. and grant N00014-17-1-2633 to G.B.D. are gratefully acknowledged. Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) athttps://data.gulfresearchinitiative.org/data/R5.x273.000:0003 (doi:10.7266/6JYHYC9W).

Publisher Copyright:
© 2020 Elsevier Ltd

Keywords

  • Bubble
  • Coalescence
  • Fragmentation
  • Lagrangian tracking
  • Optimal network
  • Pseudo-distance error

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