Print Email Facebook Twitter Modelling of NOx Emissions from Gas Turbine Combustors Title Modelling of NOx Emissions from Gas Turbine Combustors Author Maćkowiak, Marlena (TU Delft Mechanical, Maritime and Materials Engineering) Contributor Klein, S.A. (mentor) Huth, Michael (graduation committee) Meisl, Juergen (graduation committee) Degree granting institution Delft University of Technology Date 2022-11-11 Abstract The detrimental influence of nitric oxides (NOx) on humans and the environment has been widely discussed by researchers.The dominant part of nitic oxides emissions comes from combustion - majority of NOx is being produced by reaction of nitrogen and oxygen at high temperatures.This thesis project is carried out in cooperation with Siemens Energy, one of the gas turbines manufacturers.The gas turbine combustor design requires extensive work in many fields: in addition to temperature distribution and flow field prediction, modelling of acoustics and emissions is necessary. As NOx are influenced by many variables, detailed sensitivity analyses of design features is required. Since that gas turbine producers are developing their own tools for emissions predictions.The aim of this study is improvement and assessment of the existing tool used by Siemens Energy to predict NOx emissions by simulating the combustor system (both the flow and chemical kinetics).As NOx emissions depend on the air-fuel mixing quality, the tool is equipped with a Monte Carlo-based turbulent mixing model. The combustor flow is divided into small parts - particles, that react and exchange properties between each other according to the Curl's turbulent mixing model.The tool was improved by adding useful features (such as prescribed unmixedness in the flame front). After that, the Siemens Energy axially staged combustor was modelled (with different equivalence ratios, pressure levels and pilot fuel flows). In the end the tool was validated - the simulation results were compared to the experimental ones. Subject Gas TurbineCombustionMixingMonte Carlo To reference this document use: http://resolver.tudelft.nl/uuid:8ddaeffa-6139-430a-a1fd-a669eaaa18e3 Part of collection Student theses Document type master thesis Rights © 2022 Marlena Maćkowiak Files PDF MSc.Thesis_Marlena_Mackowiak.pdf 6.1 MB Close viewer /islandora/object/uuid:8ddaeffa-6139-430a-a1fd-a669eaaa18e3/datastream/OBJ/view