Journal
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
Volume 249, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jqsrt.2020.106996
Keywords
Raman spectroscopy; SERDS; Temperature; Mole fraction; Laminar flame; Bayesian inference
Categories
Funding
- German Research Foundation (DFG) within the AIF-DFG Cluster Multi-parameter characterization of particle-based functional materials by innovative online measurement technology(MPaC) [BR 3766/15-1]
- [WI 1602/14-1]
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Optical, non-invasive techniques for temperature and mole fraction measurements in flames and other reactive flows are often limited to applications under well-defined laboratory environments. These limitations mainly arise from various prerequisites of the techniques e.g. regarding the optical accessibility of the systems under investigation, its environmental conditions such as vibrations and temperature or the need of tracers inside the flow. In order to weaken these constrains, we present a robust, fiber-based sensor system, utilizing tracer-free spontaneous rotational Raman spectroscopy with tunable near-infrared (NIR) continuous-wave laser-excitation capable of a simultaneous point-wise determination of gas temperature and mole fractions in laminar spatially uniform non-sooting reactive flows. Benefits and limits of this method are evaluated investigating a laminar premixed methane/air flat-flame of a McKenna-type burner. In that case, the main rotational Raman-active and, therefore, detectable compounds are nitrogen, oxygen and carbon dioxide. For the subtraction of flame luminosity two different techniques were used: simple background subtraction (BGS) and shifted-excitation Raman difference spectroscopy (SERDS). For both methods, the corrected spectra are matched to simulated spectra via a least-square fit algorithm in order to extract the quantities of interest. Hereby, Bayesian inference enables the determination of the uncertainties of the results. The consideration of the covariance within the multi-variate analysis allows for the combination of the BGS and SERDS method to establish a more advanced analysis routine. (C) 2020 The Authors. Published by Elsevier Ltd.
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