Automatic Generation of Chemical Reactor Networks for Combustion Simulations

Abstract

Gas turbines are the power house of most modern day aircrafts. Combustion of fossil fuels provides the energy required, but this produces harmful emissions. With ever increasing strictness on emissions regulation, it is becoming even more necessary to design gas turbine combustion chambers with the intent of low pollutant output. Gas turbine engines on the other hand also have the property of dense power output, while at the same time being capable of producing lower emissions than internal combustion engines. This has served as an impetus for Mitsubishi Turbocharger and Engine Europe B.V.(MTEE), to develop a gas turbine, designed around its turbocharger unit, to be used as a range extender on Battery Electric Vehicles(BEV) in the future. The common interest of the Propulsion group at TU Delft, LR and MTEE has resulted in this thesis on researching a computational method to obtain accurate predictions of combustion emissions from a gas turbine combustor.

The method explored is the Automatic CFD-CRN method which decouples calculations of fluid mechanics and detailed chemistry by performing them in a CFD simulation and a Chemical Reactor Network respectively. Accurate prediction of emissions requires a detailed chemical kinetic mechanism to be implemented but doing so, directly in CFD, is prohibitively expensive. Hence CFD is used to obtain the combustion flow field, which is influenced mainly by the evolution of major species, whereas the minor species are obtained from the implementation of detailed chemistry in a CRN derived automatically from the CFD mesh. Such a calculation is feasible because ideal reactors, which are the building blocks of a CRN, have a simplified fluid dynamic model and can hence process the detailed chemistry at an affordable time cost.

A software package implementing the Automatic CFD-CRN process is developed and factors affecting the results from this computational tool are studied in this research work.