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Raman Scattering in Two-Phase Flows with Application to Temperature Measurements

  • S. Neti
  • C. Anastasia
  • W. Smith
  • J. C. Chen
Conference paper
Part of the International Union of Theoretical and Applied Mechanics book series (IUTAM)

Abstract

In several important applications of dispersed, two-phase flow, the possible occurrence of thermodynamic nonequilibrium between the vapor and liquid phases is of fundamental interest and practical concern. The measurement of the potential super-heated temperatures of the vapor, in the presence of colder liquid droplets remains a difficult experimental task, and to date, only partial success has been obtained by use of intrusive, aspirating thermocouple probes.

Laser Raman spectroscopy is a nonintrusive optical technique which has been developed as a diagnostic probe for gas dynamic studies. The feasibility of using Raman scattering to measure vapor temperatures in gas-liquid two-phase flows is under investigation here. A Raman system developed for the two phase measurements is described and experimentally obtained vibrational Raman bands are presented.

The Stokes vibrational Raman band was measured for single-phase steam at atmospheric pressure, with 20 to 190 K vapor superheat. Integrated intensity ratios, calculated from these spectra, are calibrated, and can be used for temperature measurements.

Water droplets, in gas-liquid two-phase samples, cause Mie and Raman scattering which interfere with the desired vapor measurement. Raman spectra, measured for atmospheric nitrogen in an air/water mist, show that Stokes vibrational spectra for the gaseous phase can be measured in dispersed two-phase samples. The principles and apparatus used for the above two-phase flow can be used for nonequilibrium two-phase flows for the measurement of vapor temperature.

Keywords

Water Droplet Raman Band Atmospheric Nitrogen Band Shape Laser Raman Spectroscopy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin, Heidelberg 1984

Authors and Affiliations

  • S. Neti
    • 1
  • C. Anastasia
    • 1
  • W. Smith
    • 1
  • J. C. Chen
    • 1
  1. 1.Institute of Thermo-Fluid Engineering & ScienceLehigh UniversityBethlehemUSA

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