Gaussian model for emission rate measurement of heated plumes using hyperspectral data

Samuel J. Grauer, Bradley M. Conrad, Rodrigo B. Miguel, Kyle J. Daun

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a novel model for measuring the emission rate of a heated gas plume using hyperspectral data from an FTIR imaging spectrometer. The radiative transfer equation (RTE) is used to relate the spectral intensity of a pixel to presumed Gaussian distributions of volume fraction and temperature within the plume, along a line-of-sight that corresponds to the pixel, whereas previous techniques exclusively presume uniform distributions for these parameters. Estimates of volume fraction and temperature are converted to a column density by integrating the local molecular density along each path. Image correlation velocimetry is then employed on raw spectral intensity images to estimate the volume-weighted normal velocity at each pixel. Finally, integrating the product of velocity and column density along a control surface yields an estimate of the instantaneous emission rate. For validation, emission rate estimates were derived from synthetic hyperspectral images of a heated methane plume, generated using data from a large-eddy simulation. Calculating the RTE with Gaussian distributions of volume fraction and temperature, instead of uniform distributions, improved the accuracy of column density measurement by 14%. Moreover, the mean methane emission rate measured using our approach was within 4% of the ground truth. These results support the use of Gaussian distributions of thermodynamic properties in calculation of the RTE for optical gas diagnostics.

Original languageEnglish (US)
Pages (from-to)125-134
Number of pages10
JournalJournal of Quantitative Spectroscopy and Radiative Transfer
Volume206
DOIs
StatePublished - Feb 2018

All Science Journal Classification (ASJC) codes

  • Radiation
  • Atomic and Molecular Physics, and Optics
  • Spectroscopy

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