4.7 Article

Fast and accurate CFD-model for NOx emission prediction during oxy-fuel combustion of natural gas using detailed chemical kinetics

期刊

FUEL
卷 264, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2019.116841

关键词

CFD NOx study; Semi-industrial burner chamber; OEC and oxy-fuel natural gas combustion; Detailed combustion chemistry

资金

  1. Austrian Research Promotion Agency (FFG)
  2. European Regional Development Fund (ERDF) [865595, 14625282, 872149, 22662407]

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Accurate prediction of NOx emission is essential in designing combustion devices and troubleshooting of existing ones. The aim of this work is to investigate the sensitivity of NOx formation during the combustion of natural gas with oxygen using a numerically inexpensive computational fluid dynamics model. To this end, an industrial jet burner was experimentally and numerically analysed for NOx formation at 600 kW controlled at 1320 and 1450 degrees C during the combustion of natural gas with pure oxygen and oxidizer mixtures containing up to 10%(nu) nitrogen. Two mixture-fraction based and two classical species transport models were investigated for their ability to: (1) predict the flame shape and temperature, (2) calculate the OH and CH emissions driving the NOx formation, and (3) fast and accurately predict the NOx emissions during oxy-fuel combustion and during the presence of low nitrogen amounts in the oxidizer. The study shows that the widely-used steady-flamelet model fails to correctly predict the flame shape and temperature, due to a too low velocity difference between the oxidizer and the fuel. It is highlighted that only the partially-premixed steady flamelet model predicted the flame shape and the NOx formation rates adequately, fitting the experimental and numerical data closely. Moreover, the shear rate in the annular gap was identified as a crucial parameter for the applicability of mixture fraction-based models. Species transport models should be used for validity checks but they disqualify as fast-solving alternatives due to their high computational demand (EDC) or lack of detailed chemistry interaction (EDM).

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