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Experimental Research and Mathematical Modelling for Coal Reburning in Furnace

机译:炉内燃煤再燃的实验研究与数学建模

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Reburning technology is one of the most cost-effective NO_X reduction strategies for coal combustion systems. In this paper, a nitric oxide submodel incorporated into a comprehensive coal combustion model was developed for predicting NO_X reduction in a 93 kW laboratory-scale coal combustion furnace by reburning. This NO submodel, including reburning mechanism, requires the solution of only two transport equations to model the behavior of NO reduction in the reburning process. A number of experiments have been performed in the same furnace, and the experimental data obtained from the optimized reburn configuration was used to validate the model. Measurements and predictions both show above 50 percent reduction of NO emissions for the optimized reburning process. Profile comparisons show that the predicted temperature and oxygen concentration match well with the measurements, and the general trend of predicted NO concentration is very similar to that measured. The results of this study show that the present nitric oxide submodel depicts quite well the observed behaviour of NO annihilation in the reburning process. It is expected that this usable and computationally economic model represents a useful tool to simulate the gaseous fuel reburning process for the researchers concerned with practical combustors.
机译:再燃技术是用于煤燃烧系统的最具成本效益的NO_X减排策略之一。在本文中,开发了一种用于综合煤燃烧模型的一氧化氮子模型,用于预测93 kW实验室规模煤燃烧炉中的NO_X通过再燃烧的还原量。这个NO子模型,包括再燃机理,只需要两个运输方程的解就可以模拟再燃过程中NO还原的行为。在同一炉中进行了许多实验,并使用从优化的再燃配置获得的实验数据来验证模型。测量和预测均显示,对于优化的再燃过程,NO排放降低了50%以上。轮廓比较显示,预测的温度和氧气浓度与测量值非常吻合,并且预测的NO浓度的总体趋势与测量值非常相似。这项研究的结果表明,当前的一氧化氮子模型很好地描述了在再燃烧过程中观察到的NO ation灭行为。期望对于实用燃烧器的研究人员来说,这种可用的,计算上的经济模型代表了一种模拟气体燃料再燃烧过程的有用工具。

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