Chemiluminescence-based multivariate sensing of local equivalence ratios in premixed atmospheric methane-air flames
Chemiluminescence emissions from OH*, CH*, C2, and CO2 formed within the reaction zone of premixed flames depend upon the fuel-air equivalence ratio in the burning mixture. In the present paper, a new partial least square regression (PLS-R) based multivariate sensing methodology is investigated and compared with an OH*/CH* intensity ratio-based calibration model for sensing equivalence ratio in atmospheric methane-air premixed flames. Five replications of spectral data at nine different equivalence ratios ranging from 0.73 to 1.48 were used in the calibration of both models. During model development, the PLS-R model was initially validated with the calibration data set using the leave-one-out cross validation technique. Since the PLS-R model used the entire raw spectral intensities, it did not need the nonlinear background subtraction of CO2 emission that is required for typical OH*/CH* intensity ratio calibrations. An unbiased spectral data set (not used in the PLS-R model development), for 28 different equivalence ratio conditions ranging from 0.71 to 1.67, was used to predict equivalence ratios using the PLS-R and the intensity ratio calibration models. It was found that the equivalence ratios predicted with the PLS-R based multivariate calibration model matched the experimentally measured equivalence ratios within 7%; whereas, the OH*/CH* intensity ratio calibration grossly underpredicted equivalence ratios in comparison to measured equivalence ratios, especially under rich conditions ( > 1.2). The practical implications of the chemiluminescence-based multivariate equivalence ratio sensing methodology are also discussed.
- Research Organization:
- Mississippi State Univ., Starkville, MS (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- FG36-06GO86025
- OSTI ID:
- 1079594
- Report Number(s):
- GO8602560
- Journal Information:
- Fuel, Vol. 93; ISSN 0016-2361
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
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