Although various
NO
x
removal technologies
have been commercialized, NO
x
emissions
are still so high that they cannot meet the newest standard and endanger
the eco-environment and human health. Meanwhile, some NO
x
reduction technologies suffer from high costs. Recently,
a cheap and pending technology called gas-fired coal preheating has
surfaced again. This method introduces hot flue gas to heat a coal
stream to high temperatures before the coal stream is injected into
a utility boiler for combustion, thus resulting in a reduction in
NO
x
. Considering the complex mechanisms
during preheating, the effect of the preheating parameters, including
temperature, residence time, excess air ratio, and coal type, are
studied in a laboratory-scale drop-tube furnace in detail. Meanwhile,
by means of Chemkin coupled with the mature NO
x
reduction mechanisms of GRI-mesh3.0 and Dagaut, as well as
a CPD model, a detailed kinetics analysis on NO removal, including
the migration and transformation of hydrocarbons and nitrogenous compounds
during PC preheating, is performed. The research provides intuitive
guidance, in practice, and a new scientific interpretation, in theory,
for NO
x
reduction during PC combustion
with preheating.
In order to achieve the accuracy of gas emission prediction for different workplaces in coal mines, three coal mining workings and four intake and return air roadway of working face in Nantun coal mine were selected for the study. A prediction model of gas emission volume based on the grey prediction model GM (1,1) was established. By comparing the predicted and actual values of gas emission rate at different working face locations, the prediction error of the gray prediction model was calculated, and the applicability and accuracy of the gray prediction method in the prediction of gas gushing out from working faces in coal mines were determined. The results show that the maximum error between the predicted and actual measured values of the gray model is 2.41%, and the minimum value is only 0.07%. There is no significant prediction error over a larger time scale; the overall prediction accuracy is high. It achieves the purpose of accurately predicting the amount of gas gushing from the working face within a short period of time. Consequently, the grey prediction model is of great significance in ensuring the safety production of coal mine working face and promote the safety management of coal mine.
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