A chemical reactor network for oxides of nitrogen emission prediction in gas turbine combustor

2014 ◽  
Vol 23 (3) ◽  
pp. 279-284 ◽  
Author(s):  
Nguyen Thanh Hao
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):  
Jian Li ◽  
Zhitao Wang ◽  
Tielei Li ◽  
Shuying Li

Abstract With the global warming, many countries pay more attention to environmental pollution. The NOx emissions has become an important index when gas turbine designed. This paper provides a method for predicting NOx emissions of marine gas turbine under variable operating conditions. Firstly build the 3-D model of combustor. The characteristic regions of combustor were divided according to the reaction principle. Then build the chemical reactor network (CRN) models of different characteristic regions. According to the NOx emissions of several specific operating points simulated by computational fluid dynamics (CFD), fit the relation between residence time and operating conditions by Newton interpolation in the CRN models. Then the prediction model of NOx emissions of gas turbine was established by using neural network. The NOx emissions under 0.7∼1.0 working conditions and 0.019∼0.023 fuel-air ratios can be predicted efficiently.


Author(s):  
Jacob Rivera ◽  
Robert Gordon ◽  
Mohsen Talei ◽  
Gilles Bourque

Abstract This paper reports on an optimisation study of the CO turndown behaviour of an axially staged combustor, in the context of industrial gas turbines (GT). The aim of this work is to assess the optimally achievable CO turndown behaviour limit given system and operating characteristics, without considering flow-induced behaviours such as mixing quality and flame spatial characteristics. To that end, chemical reactor network modelling is used to investigate the impact of various system and operating conditions on the exhaust CO emissions of each combustion stage, as well as at the combustor exit. Different combustor residence time combinations are explored to determine their contribution to the exhaust CO emissions.


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