With the global warming, many countries pay more and more attention to environmental pollution. How to reduce industrial emissions has become a hot issue that must be paid attention to. The gas turbine is an important part in the field of energy power equipment. With the increasing attention to environmental pollution, gas turbine emission is taken more seriously. NO~x~ emission performance has become an important index of designing the gas turbine.

At present, CFD and other numerical simulation software are generally used to predict gas turbine combustion emissions. The prediction results obtained by this method are accurate but less efficient.

And it can only be used to predict the design working conditions,but cannot be applied to the variable working conditions. With different boundary conditions and different working conditions, gas turbines have a very diverse and complicated running state.It is also important to predict the emission performance under these operating conditions.

This brief reports a method to predict NO~x~ emission performance of marine gas turbine under variable operating conditions.In this method, the fluent was used to build the model of combustion chamber. The characteristic regions of combustion chamber were divided according to the reaction principle. Then combined with the chemkin-pro software, a gas turbine combustor chemical reactor network (CRN) model was established to calculate the NO~x~ emission performance in the design condition. The method of newton interpolation polynomial was used to predict NO~x~ emission performance in other conditions. Then the prediction model of NO~x~ emission of gas turbine was established by using neural network. To realize fast and accurate prediction of NO~x~ emission performance of marine gas turbine under operating conditions from 0.7 to 1.0 and fuel - air ratio from 0.019 to 0.023.


Research on Prediction of NOX Emission Performance of Marine Gas Turbine Under Variable Operating Conditions

Division / Sponsor:
International Gas Turbine Institute (IGTI)

Paper Proceedings: https://asmedigitalcollection.asme.org/GT/GT2020/volume/84058

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