Pilot-Scale Study on Improving SNCR Denitrification Efficiency by Using Gas Additives

2018 ◽  
Vol 17 (3) ◽  
Author(s):  
Zhou Weiqing ◽  
Liu Meng ◽  
Huang Baohua ◽  
Qiu Xiaozhi
Keyword(s):  
Low Temperature ◽  
Fluidized Bed ◽  
Reaction Temperature ◽  
Temperature Region ◽  
Circulating Fluidized Bed ◽  
Catalytic Reduction ◽  
Pilot Scale ◽  
Incomplete Oxidation ◽  
Optimal Value

Abstract The experiment of improving Selective Non-Catalytic Reduction (SNCR) denitrification efficiency with gas additives (CH4 and C3H8) was carried out in the 50 kW circulating fluidized bed (CFB) pilot-scale equipment. The results show that the denitrification efficiency can reach 20 % when the reaction temperature is 650 °C, and the optimum mole ratio of C3H8/NH3 is 0.5. The denitrification efficiency can exceed 50 % when the mole ratio of C3H8/NH3 is 0.4 and the reaction temperature is 720 °C. However, the CH4 additive does not promote denitrification at this temperature. When the reaction temperature is 760 °C, the optimum denitrification efficiency of CH4 is 60 %, and the required CH4/NH3 is 0.8. Once the amount of CH4 exceeds the optimal value, the denitrification efficiency is suppressed. In addition, the concentrations of N2O and CO in the gas increase significantly with an increase of gas additives. Due to the incomplete oxidation of C3H8, a large amount of C2H4 is produced in the low-temperature region (< 750 °C) of SNCR.

Carbon dioxide purity and combustion characteristics of oxy firing compared to air firing in a pilot-scale circulating fluidized bed

Energy ◽  
2019 ◽  
Vol 166 ◽  
pp. 183-192 ◽  
Author(s):  
Ji-Hong Moon ◽  
Sung-Ho Jo ◽  
Sung Jin Park ◽  
Nguyen Hoang Khoi ◽  
Myung Won Seo ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Pilot Scale ◽  
Combustion Characteristics

scholarly journals Climate effect of an integrated wheat production and bioenergy system with Low Temperature Circulating Fluidized Bed gasifier

2015 ◽  
Vol 160 ◽  
pp. 511-520 ◽  
Author(s):  
Hafthor Ægir Sigurjonsson ◽  
Brian Elmegaard ◽  
Lasse Røngaard Clausen ◽  
Jesper Ahrenfeldt
Keyword(s):  
Low Temperature ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Climate Effect ◽  
Wheat Production ◽  
Fluidized Bed Gasifier

Applications of Feed-Forward Neural Network to Study Irregular-Shape Particle Effects on Hydrodynamics Behavior in a Liquid–Solid Circulating Fluidized Bed Riser

2013 ◽  
Vol 11 (1) ◽  
pp. 443-452 ◽  
Author(s):  
Shaikh Abdur Razzak
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Phase Distribution ◽  
Flow Behavior ◽  
Pilot Scale ◽  
Irregular Shape ◽  
Feed Forward Neural Network ◽  
Feed Forward

Abstract Feed-forward neural network (FFNN) modeling techniques are applied to study the flow behavior of different-size irregular-shape particles in a pilot scale liquid–solid circulating fluidized bed (LSCFB) riser. The adequacy of the developed model is examined by comparing the model predictions with experimental data obtained from the LSCFB using lava rocks (dmean 500 and 920 µm) and water as solids and liquid phases, respectively. Axial and radial solid holdup profiles are measured in the riser at four axial locations (H 1, 2, 3 and 3.8 m above the distributor) above the liquid distributor for different operating liquids. In the model training, the effects of various auxiliary and primary liquid velocities, superficial liquid velocities and superficial solid velocities on radial phase distribution at different axial positions are considered. For model validation along with other experimental parameters, dimensionless normalized superficial liquid velocities and net superficial liquid velocities are also introduced. The correlation coefficient values of the predicted output and the experimental data are found to be 0.95 and 0.94 for LR-500 and LR-920 particles, respectively which reflects the competency of the developed FFNN model.

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