A Reduced Kinetic Model for NO<i><sub>x</sub></i> Reduction by Advanced Reburning

Hong, Xu; Smoot, L.D.; Hill, Scott C.

doi:10.1021/ef980084l

Cited by 12 publications

(25 citation statements)

References 14 publications

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“…Comprehensive modeling of the CPR for comparison with the measured data has been attempted using PCGC-3, a comprehensive pulverized coal combustion model developed at Brigham Young University by the Advanced Combustion Engineering Research Center (ACERC). The code has recently be upgraded to include subroutines for reburning and advanced reburning as described by Xu and Smoot (1998) and Xu and Smoot (1999). Additionally, a commercial combustion code, FLUENT, has been used for comparison with the flow exiting the primary reaction zone.…”

Section: Modeling Resultsmentioning

confidence: 99%

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Tree¹

1999

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Nitrogen oxide emissions from pulverized coal combustion have been and will continue to be a regulated pollutant for electric utility boilers burning pulverized coal. Full scale combustion models can help in the design of new boilers and boiler retrofits which meet emissions standards, but these models require validation before they can be used with confidence. The objective of this work was to obtain detailed combustion measurements of pulverized coal flames which implement two NO reduction strategies, namely reburning and advanced reburning, to provide data for model validation. The data were also compared to an existing comprehensive pulverized coal combustion model with a reduced mechanism for NO reduction under reburning and advanced reburning conditions. The data were obtained in a 0.2 MW, cylindrical, down-fired, variable swirl, pulverized coal reactor. The reactor had a diameter of 0.76 m and a length of 2.4 m with access ports along the axial length. A Wyodak, sub-bituminous coal was used in all of the measurements. The burner had a centrally located primary fuel and air tube surrounded by heated and variably swirled secondary air. Species of NO, NO x , CO, CO 2 and O 2 were measured continuously. Aqueous sampling was used to measure HCN and NH 3 at specific reactor locations. Samples were drawn from the reactor using water quenched suction probes. Velocity measurements were obtained using two component laser doppler anemometry in back-scatter mode. Temperature measurements were obtained using a shielded suction pyrometer. A series of six or more radial measurements at six or more axial locations within the reactor provided a map of species, temperature, and velocity measurements. In total, seven reactor maps were obtained. Three maps were obtained at baseline conditions of 0, 0.5 and 1.5 swirl and 10% excess air. Two maps were obtained under reburning conditions of 0.78 stoichiometric ratio and 1.5 swirl and 0.9 stoichiometric ratio and 0.5 swirl. And finally, two maps were obtained under advanced reburning conditions both at the same operating condition of 1.05 stoichiometric ratio in the reburning zone followed by ammonia injection. Numerous effluent measurements were obtained to study the affect of natural gas injection location, stoichiometric ratio, and injection velocity on effluent NO. For advanced reburning, effluent measurements were obtained for a similar matrix of operating conditions with the additional variable of ammonia nitrogen to nitrogen in NO or nitrogen stoichiometric ratio (NSR). Baseline maps and effluent measurements were useful in establishing the flow patterns of the reactor and determining the effect of swirl on NO. At zero swirl the flame appeared to be lifted and therefore created higher NO. At 0.5 swirl the flame had transitioned to an attached flame with a central recirculation zone and produced lower NO. Detailed velocity measurements of the quarl were obtained which provided boundary conditions for modeling and helped explain why the flame was not attached at zero swirl. ...

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Section: Modeling Resultsmentioning

confidence: 99%

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Tree¹

1999

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“…For minor species, such as OH, H and CH 4 , errors are a little larger though profile agreements are still preserved. Predicted profiles of other involved species represent similar features even if not shown in figure. Comparatively scalar errors are a little larger in C 3 H 8 /air case than those in H 2 /air case due to inclusion of kinetics reduction process, but by referring to the errors resulting from traditional reduced mechanism [9,[28][29][30][31], the error magnitude is quite acceptable. Overall, the ANN-based method for chemical kinetics reduction can well replicate the flame dynamics in FVI at the influence of different vortex.…”

Section: Fvi Testmentioning

confidence: 96%

Systematic method of applying ANN for chemical kinetics reduction in turbulent premixed combustion modeling

Zhao

Wang

et al. 2012

Chin. Sci. Bull.

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A novel method to apply artificial neural network (ANN) for both chemical kinetics reduction and source term evaluation is introduced and tested in direct numerical simulation (DNS) and large eddy simulation (LES) of reactive flows. To gather turbulence affected flame data for ANN training, a new computation-economical method, called 1D pseudo-velocity disturbed flame (PVDF), is developed and used to generate thermo-chemical states independent of the modeled flame. Then a back-propagation ANN is trained using scaled conjugate gradient algorithm to memorize the sample states with reduced orders. The new method is employed in DNS and LES modeling of H 2 /air and C 3 H 8 /air premixed flames experiencing various levels of turbulence. The test result shows that compared to traditional computation with full mechanism and direct integration, this method can obtain quite large speed-ups with adequate prediction accuracy. [7,8] are often used, while ANN method, a extremely new systemic technique, is seldom seen in previous work. The procedure of using QSS assumption has been shown in Figure 1. However, QSS species concentrations should be first resolved which includes a large amount of algebraic iterations. Therefore, the net efficiency could be undermined [9], and also calculation may be failed if iterations do not converge. ANN, kinetics reduction, LES, DNSAs for the second respect, several approaches to accelerate chemical sources evaluation have already been presented, such as look-up table (LUT) [10] and in situ-adaptive tabulation (ISAT) [11]. However, they are both based on tabulation technique which needs huge memory and a large number of check-up and interpolation operations. Artificial neural network (ANN) method, although it was proposed previously to handle above drawbacks, has got great progress through Sen and Menon's work [12,13]. It has been successfully applied to account for chemical kinetics in LES modeling of turbulent premixed flame with speed-ups even more than 10.In this paper, we tend to extend the application of ANN method, using it to not only calculate chemical sources but also reduce the detailed mechanism. The initial idea is to construct the direct mapping between non-QSS species concentrations and their reaction rates at plenty of thermal

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“…are air staging, 8,9 temperature adjustment, 10 selective noncatalytic reduction (SNCR), 11 lowering excess air, 12 reburning (fuel staging), 13,14 flue gas recirculation, 15 and fuel blending. 16,17 Hybrid systems such as SNCR, air staging, 11 and reburning combined with SNCR (advanced reburning) 18,19 have also been investigated. In comparison, countermeasures against bed agglomeration include the use of alternative bed materials, 7,20,21 additives, 22,23 cocombustion, 7,24 and biomass pretreatment.…”

Section: Introductionmentioning

confidence: 99%

Multifunctional Additives for NO_X Abatement in Fluidized Bed Biomass Combustion

et al. 2021

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Two major challenges in fluid bed combustion of biomass are increased NO X emissions and bed agglomeration. Different additives were employed to simultaneously reduce NO X emissions and bed agglomeration from the fluidized bed combustion of biomass. The base fuel was straw, and the additives included CaO, kaolin, MgCO 3 , coal fly ash, clay, (NH 4 ) 2 Fe(SO 4 ) 2 , NH 4 Fe(SO 4 ) 2 , (NH 4 ) 2 SO 4 , NH 4 MgPO 4 , AlNH 4 (SO 4 ) 2 , (NH 4 ) 2 HPO 4 , (NH 4 ) 3 [Fe(C 2 O 4 ) 3 ], and urea. The influence of (NH 4 ) 2 SO 4 particle size (<35 and <106 μm) and introduction method (batch addition or premixing with fuel) was additionally investigated. The most effective additives against NO X emissions and bed agglomeration were further studied in air staged straw combustion and unstaged sunflower husk combustion. During sunflower husk combustion, the influence of ash accumulation and incipient defluidization on NO X emissions were examined. The results show that kaolin, CaO, MgCO 3 , (NH 4 ) 2 Fe(SO 4 ) 2 , NH 4 Fe(SO 4 ) 2 , AlNH 4 (SO 4 ) 2 , and NH 4 MgPO 4 prevented defluidization during straw combustion under the investigated conditions. Of these, AlNH 4 (SO 4 ) 2 and NH 4 MgPO 4 reduced the fuel-N to NO conversion by 40%. The mechanism of reduction was related to the facilitation of thermal DeNO X reactions by the introduction of NH 3 -releasing additives. However, the NH-based additives resulted in higher emissions of N 2 O. The size of (NH 4 ) 2 SO 4 particles had a slight influence on the defluidization tendency and nitrogen chemistry, while no significant difference was observed between the two additive introduction methods. Air staging reduced the fuel-N to NO conversion by 40% during straw combustion. The use of NH 4 MgPO 4 and AlNH 4 (SO 4 ) 2 under air staged conditions increased the NO emission slightly. This was predominantly caused by the combustion of NH 3 in the secondary air jet. In the case of unstaged sunflower husk combustion, NH 4 MgPO 4 and AlNH 4 (SO 4 ) 2 prevented defluidization while reducing the conversion of fuel-N to NO by 30%. During sunflower husk combustion, the accumulation of ash increased NO and decreased NH 3 concentrations above the bed. This was related to the poor mixing as the bed approached defluidization and to the catalytic effect of ash forming elements on the oxidation of NH 3 to NO.

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A Reduced Kinetic Model for NO_x Reduction by Advanced Reburning

Cited by 12 publications

References 14 publications

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Systematic method of applying ANN for chemical kinetics reduction in turbulent premixed combustion modeling

Multifunctional Additives for NO_X Abatement in Fluidized Bed Biomass Combustion

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A Reduced Kinetic Model for NOx Reduction by Advanced Reburning

Cited by 12 publications

References 14 publications

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Temperature, velocity and species profile measurements for reburning in a pulverized, entrained flow, coal combustor

Systematic method of applying ANN for chemical kinetics reduction in turbulent premixed combustion modeling

Multifunctional Additives for NOX Abatement in Fluidized Bed Biomass Combustion

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Product

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A Reduced Kinetic Model for NO_x Reduction by Advanced Reburning

Multifunctional Additives for NO_X Abatement in Fluidized Bed Biomass Combustion