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Optimization of ammonia injection grid in hybrid selective non-catalyst reduction and selective catalyst reduction system to achieve ultra-low NOx emissions.

Authors :
Zhou, Hao
Guo, Xutao
Zhou, Mingxi
Ma, Weiwei
Dahri, Muhammad Waryal
Cen, Kefa
Source :
Journal of the Energy Institute (Elsevier Science); Dec2018, Vol. 91 Issue 6, p984-996, 13p
Publication Year :
2018

Abstract

Abstract The uniformity of NH 3 in the flue gas is the main factor improving the efficiency during the hybrid selective non-catalytic reduction (SNCR)-selective catalytic reduction (SCR) denitrification process. This work presents the optimized ammonia injection grid (AIG) to enhance the mixing performance and optimize concentration uniformity. A testing ammonia injected facility with a scale of 1:1 is established to experimentally simulate the NH 3 mixing behavior in the tail flue gas duct employing the tracer gas. A novel injection grid with multiple inclined nozzles is proposed to replace the conventional direct-injection type. The flow field and tracer gas concentration field are studied under the three conditions with various inclined jet angles including 0°, 30° and 45°. From results, mixing enhancement between jet and crossflow for the inclined injection grid is achieved. It is also indicated that the inclined angle plays an important effect on jet rigidity and tracer gas dilution. The flow field and tracer gas mixing performances are quantitatively analyzed by using the root mean square deviation coefficient. Multiple jets with an inclined angle of 30° achieved the best mixing performance. Consequently, optimized AIG design has shown effective NO x control performance in industrial utility furnace. Highlights • Multiple inclined jets are proposed to replace the conventional direct-injection type. • Improve the velocity and concentration distribution uniformity. • Optimized ammonia injection grid has been applied in industrial utility furnace. • Achieve the requirement of NO x emission concentration lower than 50 mg/Nm<superscript>3</superscript>. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17439671
Volume :
91
Issue :
6
Database :
Complementary Index
Journal :
Journal of the Energy Institute (Elsevier Science)
Publication Type :
Academic Journal
Accession number :
132970180
Full Text :
https://doi.org/10.1016/j.joei.2017.07.009