Improved Chemical Reactor Network Application for Predicting the Emission of Nitrogen Oxides in a Lean Premixed Gas Turbine Combustor

2019 ◽  
Vol 55 (3) ◽  
pp. 267-273 ◽  
Author(s):  
T. H. Nguyen
2013 ◽  
Vol 27 (3) ◽  
pp. 1643-1651 ◽  
Author(s):  
Jungkyu Park ◽  
Truc Huu Nguyen ◽  
Daero Joung ◽  
Kang Yul Huh ◽  
Min Chul Lee

2020 ◽  
Vol 24 (3 Part B) ◽  
pp. 1977-1989
Author(s):  
Seyfettin Hataysal ◽  
Ahmet Yozgatligil

Gas turbine combustor performance was explored by utilizing a 1-D flow network model. To obtain the preliminary performance of combustion chamber, three different flow network solvers were coupled with a chemical reactor network scheme. These flow solvers were developed via simplified, segregated and direct solutions of the nodal equations. Flow models were utilized to predict the flow field, pressure, density and temperature distribution inside the chamber network. The network model followed a segregated flow and chemical network scheme, and could supply information about the pressure drop, nodal pressure, average temperature, species distribution, and flow split. For the verification of the model?s results, analyses were performed using CFD on a seven-stage annular test combustor from TUSAS Engine Industries, and the results were then compared with actual performance tests of the combustor. The results showed that the preliminary performance predictor code accurately estimated the flow distribution. Pressure distribution was also consistent with the CFD results, but with varying levels of conformity. The same was true for the average temperature predictions of the inner combustor at the dilution and exit zones. However, the reactor network predicted higher elemental temperatures at the entry zones.


Author(s):  
I. V. Novosselov ◽  
P. C. Malte ◽  
S. Yuan ◽  
R. Srinivasan ◽  
J. C. Y. Lee

A chemical reactor network (CRN) is developed and applied to a dry low emissions (DLE) industrial gas turbine combustor with the purpose of predicting exhaust emissions. The development of the CRN model is guided by reacting flow computational fluid dynamics (CFD) using the University of Washington (UW) eight-step global mechanism. The network consists of 31 chemical reactor elements representing the different flow and reaction zones of the combustor. The CRN is exercised for full load operating conditions with variable pilot flows ranging from 35% to 200% of the neutral pilot. The NOpilot. The NOx and the CO emissions are predicted using the full GRI 3.0 chemical kinetic mechanism in the CRN. The CRN results closely match the actual engine test rig emissions output. Additional work is ongoing and the results from this ongoing research will be presented in future publications.


Author(s):  
Igor V. Novosselov ◽  
Philip C. Malte

In this paper, the development of an eight-step global chemical kinetic mechanism for methane oxidation with nitric oxide formation in lean-premixed combustion at elevated pressures is described and applied. In particular, the mechanism has been developed for use in computational fluid dynamics (CFD) and chemical reactor network (CRN) simulations of combustion in lean-premixed gas turbine engines. Special attention is focused on the ability of the mechanism to predict NOx and CO exhaust emissions. Applications of the eight-step mechanism are reported in the paper, all for high-pressure, lean-premixed, methane-air (or natural gas-air) combustion. The eight steps of the mechanism are as follows: 1. Oxidation of the methane fuel to CO and H2O. 2. Oxidation of the CO to CO2. 3. Dissociation of the CO2 to CO. 4. Flame NO formation by the Zeldovich and nitrous oxide mechanisms. 5. Flame NO formation by the prompt and NNH mechanisms. 6. Post-flame NO formation by equilibrium H-atom attack on equilibrium N2O. 7. Post-flame NO formation by equilibrium O-atom attack on equilibrium N2O. 8. Post-flame Zeldovich NO formation by equilibrium O-atom attack on N2.


Author(s):  
Candy Hernandez ◽  
Vincent McDonell

Abstract Lean-premixed (LPM) gas turbines have been developed for stationary power generation in efforts to reduce emissions due to strict air quality standards. Lean-premixed operation is beneficial as it reduces combustor temperatures, thus decreasing NOx formation and unburned hydrocarbons. However, tradeoffs occur between system performance and turbine emissions. Efforts to minimize tradeoffs between stability and emissions include the addition of hydrogen to natural gas, a common fuel used in stationary gas turbines. The addition of hydrogen is promising for both increasing combustor stability and further reducing emissions because of its wide flammability limits allowing for lower temperature operation, and lack of carbon molecules. Other efforts to increase gas turbine stability include the usage of a non-lean pilot flame to assist in stabilizing the main flame. By varying fuel composition for both the main and piloted flows of a gas turbine combustor, the effect of hydrogen addition on performance and emissions can be systematically evaluated. In the present work, computational fluid dynamics (CFD) and chemical reactor networks (CRN) are created to evaluate stability (LBO) and emissions of a gas turbine combustor by utilizing fuel and flow rate conditions from former hydrogen and natural gas experimental results. With CFD and CRN analysis, the optimization of parameters between fuel composition and main/pilot flow splits can provide feedback for minimizing pollutants while increasing stability limits. The results from both the gas turbine model and former experimental results can guide future gas turbine operation and design.


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