Optimization method for the component of aviation kerosene surrogate fuels based on chemical reactor network model

Author(s):  
Danwei Zheng ◽  
Yong Liu ◽  
Xiang Zhang ◽  
Zijiang Deng ◽  
Jiaman Wu
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):  
Silvio Trespi ◽  
Hendrik Nicolai ◽  
Paulo Debiagi ◽  
Johannes Janicka ◽  
Andreas Dreizler ◽  
...  

Author(s):  
Qun Zhang ◽  
Han Hai ◽  
Chengyu Li ◽  
Yuming Wang ◽  
Peng Zhang ◽  
...  

This study is aimed to establish a detailed chemical reactor network model based on the analysis of complex reaction flowfield structures in aeroengine combustors, so that the emissions of nitrogen oxides and carbon monoxide from advanced civil aeroengines can be predicted quickly and accurately. In this study, a low-emission concentric staged combustor with three axial swirlers is designed for civil aeroengines, and numerical simulations of the three-dimensional reaction flowfields of the combustor during four load phases of takeoff, climb, approach, and idle, are conducted. Based on the numerical results, a simple chemical reactor network model with seven perfectly stirred reactors and a detailed chemical reactor network model using up to 15 perfectly stirred reactors are established. Using the developed chemical reactor network models and the detailed JP10 chemical reaction mechanism—composed of 374 step elementary reactions and 82 species, the emission variations of nitrogen oxides and carbon monoxide are predicted and compared with those estimated using an empirical formula and with the numerical results as a function of the combustion load. Using a combined chemical reactor network–computational fluid dynamics analysis method, the variations of the formation path, the mechanism, and the amounts of nitrogen oxides in the combustor and in the perfectly stirred reactors, are analyzed as a function of the combustion load. In addition, the effects of fuel and air pilot-to-total ratio on nitrogen oxides emissions for the 100% load condition are also analyzed. It is found that at high loads, the production rate of the thermal NO is the highest, while at low loads, the production rate of the prompt NO is the highest. The nitrogen oxide is mainly produced in the pilot zone and the recirculation zone, while its production in the outer main stage zone is low. The results show that the NOx emissions predicted by the complex chemical reactor network model are most consistent with those elicited using the empirical formula.


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.


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