Search

Ammonia as a carbon-free fuel has great potentiality to be utilized in power generation sectors such as micro gas turbines (MGT) to mitigate carbon dioxide emission from combustion systems. It is also easy to store and transport at room temperature compared to hydrogen, and in liquid form has equal volumetric energy density to liquid hydrogen. However, some challenges regarding its NOx pollution and flame stabilization inhibit its usage in these areas which requires further studies. In the present study, thermal performance and NOx emission of an MGT combustor fueled with ammonia-natural gas blends has been analyzed numerically through chemical reactant networks (CRN). The combustor's inlet conditions are at atmospheric conditions and diffusion flame is stabilized using air swirler. In the first part of the paper, the CRN model has been developed based on empirical and semi-empirical equations. Series of experiments have been carried out to find the required parameters for the CRN model. Also, the results of NOx emission and temperature distribution have been validated with the experimental results. In the second part, effects of ammonia addition to the natural gas fuel are studied for various ammonia percentages using the CRN. The results show that by increasing ammonia molar percentage in the fuel, NO emission rises dramatically and reaches up to 330 PPM, but after a certain threshold (about 12.5 molar percent of ammonia) further ammonia addition reduces NO emission. Moreover, the overall temperature of the combustor decreases with ammonia addition due to lower LHV (lower heating value) of ammonia relative to natural gas. However, the overall efficiency of the combustor does not change significantly. The results also reveal that most of the NO is produced in the primary and secondary zones of the combustor. NO2 is mostly created in the secondary zone of the combustor and comprises about 10% of total NOx emission. [ABSTRACT FROM AUTHOR]

Chemical kinetics modeling within the numerical simulations of turbulent reactive flows is a critical issue. In this study, first a large eddy simulation of a non-premixed planar methane jet flame with artificial neural network -based chemical kinetics is performed. To consider the effects of turbulence on the evolution of the thermo-chemical state space, the artificial neural network training patterns are obtained by solving the unsteady reaction-diffusion equations of linear eddy mixing sub-grid combustion model. The optimization procedure for selecting the optimum neural network architecture is discussed in detail. A flow field analysis and a comparison between a non-reactive jet with the same velocity boundary conditions with the flame jet are performed. It is shown that the non-reactive jet is more turbulent and vortical structures of the non-reactive jet occur closer to the jet exit compared to the flame jet. Second, in a first attempt to quantify the influence of different chemical kinetics methods, large eddy simulation computations are performed with other methods used to represent the chemical kinetics such as direct integration and look-up table. A comparative study is performed between the averaged, instantaneous and fluctuation profiles of the scalar field and flame structures obtained by each method. Although all large eddy simulation results are very close to each other, the main discrepancy is observed for CO mass fractions obtained by artificial neural network and look-up table-based chemical kinetics simulations. It is also shown that the averaged scalar field and the conditional averaged values of the flame are overestimated by look-up table based chemical kinetics large eddy simulation computations. Moreover, the potential savings of artificial neural network in computational costs in comparison with other chemistry approaches are illustrated. [ABSTRACT FROM AUTHOR]