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Two-dimensional flame temperature and emissivity measurements of pulverized oxy-coal flames

Author

Listed:
  • Draper, Teri Snow
  • Zeltner, Darrel
  • Tree, Dale R.
  • Xue, Yuan
  • Tsiava, Remi

Abstract

A broadband, RGB, two-color pyrometry technique for measuring the flame temperature and total emissivity of a two-dimensional image of a coal flame has been developed and used on an oxy-coal flame. The method uses a single, relatively inexpensive, RGB, digital camera. The camera software permits the light intensities of the red, green, and blue light collected for each pixel to be recorded separately. The response of each pixel was calibrated for each color using a blackbody radiating cavity and a monochrometer, which enabled an absolute, broadband emission measurement. The image obtained by the camera was processed to produce a temperature and total emissivity for each pixel. Two spectral emissivity models were explored for use in determining the temperature and emissivity: a Gray model and Hottel and Broughton’s soot emissivity model. Significant differences of 7.1% in average temperature and 24.2% in average emissivity were found. While neither model is ideal for the entire coal flame, the Hottel and Broughton model was selected for future image processing because the images and analysis suggested soot was the more dominant emitter for most of the image. Images were obtained in a 150kWth, pulverized-coal reactor at two different mixture oxidizer ratios of O2/CO2. The addition of CO2 decreased the average flame temperature from 2183K to 2022K and reduced the average emissivity from 0.59 to 0.13. The increase in CO2 lowered the temperature by increasing the dilution. The increased flow rate caused increased mixing, which reduced soot formation and thus the emissivity.

Suggested Citation

  • Draper, Teri Snow & Zeltner, Darrel & Tree, Dale R. & Xue, Yuan & Tsiava, Remi, 2012. "Two-dimensional flame temperature and emissivity measurements of pulverized oxy-coal flames," Applied Energy, Elsevier, vol. 95(C), pages 38-44.
  • Handle: RePEc:eee:appene:v:95:y:2012:i:c:p:38-44
    DOI: 10.1016/j.apenergy.2012.01.062
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    Citations

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    Cited by:

    1. Pourhoseini, S.H., 2017. "A novel configuration of natural gas diffusion burners to enhance optical, thermal and radiative characteristics of flame and reduce NOx emission," Energy, Elsevier, vol. 132(C), pages 41-48.
    2. Weijie Yan & Yunqi Ya & Feng Du & Hao Shao & Peitao Zhao, 2017. "Spectrometer-Based Line-of-Sight Temperature Measurements during Alkali-Pulverized Coal Combustion in a Power Station Boiler," Energies, MDPI, vol. 10(9), pages 1-14, September.
    3. Weijie Yan & Dongmei Chen & Zuomei Yang & Enyu Yan & Peitao Zhao, 2017. "Measurement of Soot Volume Fraction and Temperature for Oxygen-Enriched Ethylene Combustion Based on Flame Image Processing," Energies, MDPI, vol. 10(6), pages 1-16, May.
    4. Chen, Junghui & Chan, Lester Lik Teck & Cheng, Yi-Cheng, 2013. "Gaussian process regression based optimal design of combustion systems using flame images," Applied Energy, Elsevier, vol. 111(C), pages 153-160.
    5. Zhou, Dongdong & Cheng, Shusen, 2019. "Measurement study of the PCI process on the temperature distribution in raceway zone of blast furnace by using digital imaging techniques," Energy, Elsevier, vol. 174(C), pages 814-822.
    6. Pourhoseini, S.H., 2020. "Enhancement of radiation characteristics and reduction of NOx emission in natural gas flame through silver-water nanofluid injection," Energy, Elsevier, vol. 194(C).
    7. Ren, Tao & Modest, Michael F. & Fateev, Alexander & Sutton, Gavin & Zhao, Weijie & Rusu, Florin, 2019. "Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

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