Network Modeling Application to Laminar Flame Speed and NO_x Prediction in Industrial Gas Turbines

Sammanfattning:

The arising environmental concerns make emission reduction from combustion devices one of the greatest challenges of the century. Modern dry low-NO_x emission combustion systems often operate under lean premixed turbulent conditions. In order to design and operate these systems efficiently, it is necessary to have a thorough understanding of combustion process in these devices.

In premixed combustion, flame speed determines the conversion rate of fuel. The flame speed under highly turbulent conditions is defined as turbulent flame speed. Turbulent flame speed depends on laminar flame speed, which is a property of the combustible mixture.

The goal of this thesis is to estimate laminar flame speed and NO_x emissions under certain conditions for specific industrial gas turbines. For this purpose, an in-house one-dimensional code, GENE-AC, is used.

At first, a data validation is performed in order to select an optimized chemical reaction mechanism which can be used safely with the fuels of interest in gas turbines. Results show that GRI-Mech 3.0 performs well in most cases. This mechanism is selected for further simulations.

Secondly, laminar flame speed is calculated using GRI-Mech 3.0 at SGT-800 conditions. Results show that at gas turbine conditions, increasing ambient temperature and fuel to air ratio enhances flame speed, mainly due to faster reaction rates. Moreover, laminar flame speed is highly affected by fuel composition. In particular, adding hydrogen to a fuel changes chemical processes significantly, because hydrogen is relatively light and highly diffusive. Calculations are conducted over a range of equivalence ratios and hydrogen fractions in methane at atmospheric as well as gas turbine operating conditions. Results reveal some trends for changes in laminar flame speed, depending on hydrogen content in the mixture.

The final part of the thesis involves the development of a reactor network model for the SGT-700 combustor in order to predict NO_x emissions. The network model is built in GENE-AC based on results from available computational fluid dynamics (CFD) simulations of the combustor. The model is developed for full load conditions with variable pilot fuel ratios. The NO_x emissions are predicted using GRI-Mech 3.0 mechanism. A parametric study shows the dependency of NO_x emissions on equivalence ratio and residence time. For SGT-700 running on natural gas, NO_x emissions are fitted to measurement data by tuning equivalence ratio and residence time. The model is then tested for a range of ambient temperatures and fuel compositions. It is found that, although the model can correctly predict the trends of ambient temperature and fuel effects on NO_x emissions, these effects are to some extent over-estimated. Using future engine tests and amending calibration can improve the results.