Prediction of emissions from combustion systems is a complex problem involving the coupling between the flow field and chemistry. CFD analysis is the most commonly employed approach. However, it has the drawback that a very high computational cost prevents the use of detailed chemistry models. This master thesis, which focuses on NOx emissions, uses a more unconventional method of emissions prediction: Chemical Reactor Network (CRN). The advantage of this method is that, as it does not use fine discretisation, closure models nor fluid dynamics equations, it allows the implementation of detailed chemistry mechanisms.

A CRN is developed first for a single-element Lean Direct Injection (LDI) combustor and then the CRN is adapted for a Multi-Point LDI (MPLDI) combustor. CFD and experimental results are used to set up the CRN. In the base case scenario, in which kerosene is the fuel choice, the NOx emissions predicted are very close to experimental measurements. This is particularly meaningful given the high uncertainties of modelling this highly complex turbulent combustion process.

The developed CRN is also used to predict NOx emissions for the same combustor when the fuel choice is varied. Namely, the alternative fuels considered are kerosene enriched with hydrogen, methane and methane enriched with hydrogen. In comparison to kerosene, higher Lower Heating Values (LHVs) of these fuels lead to lower combustor temperatures for the same power input. Consequently, the thermal NOx pathway is weakened and the NOx mass flow generated is reduced. Nevertheless, these fuels with a higher LHV come with an increased operational risk that must be overcome before their implementation in aviation becomes possible.