DNS-driven development of predictive LES models for gas turbine emissions

• Applicant: Professor Dr.-Ing. Heinz Pitsch
• Subject Area: Energy Process Engineering
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 434872808

The reduction of pollutant emissions is one of the main challenges in the development of gas turbine combustors. In this context, large-eddy simulations (LES), can contribute to reducing development cost and accelerating development processes. Therefore, the aim of this project is the improvement of emission models for LES of both aeroengines and stationary gas turbines. The present proposal is for the second phase of a 2+2-year project. For aeroengines, the focus is on modeling of soot. After soot formation and oxidation have been investigated in the first project phase, a better understanding for the breakthrough of soot from rich to fuel-lean regions is intended in the second phase. Soot breakthrough occurs when, due to the high turbulence levels in aeroengines, turbulent eddies transport soot pockets from fuel rich regions through the flame to fuel lean regions fast enough that a complete oxidation of soot particles cannot take place. Current LES models cannot describe these events with sufficient accuracy, thus significantly underpredicting soot emissions. In this project, state of the art LES models available in the literature and developed in previous project phases will be extended to consider soot breakthrough phenomena. This will be done in a three-step process: 1) generation of a DNS data base for three different levels of soot breakthrough; 2) assessment of current models based on the DNS and development of model extensions considering soot breakthrough; 3) model validation via LES of a lab-scale jet flame configuration and of a full model combustor. In stationary gas turbines, carbon monoxide (CO) emissions will be investigated. The aim in this phase is to study the effect of the hydrogen (H2) addition to methane (CH4) on CO emissions and their modeling. Starting point is the importance of H2 as future energy carrier. Here, we will consider the addition of small amounts of H2 to natural gas as fuel in stationary gas turbines. Previous work has shown the ability of even small amounts of H2 to significantly reduce CO emissions as a result of the increased flame speeds. A series of DNS of turbulent combustion of CH4/H2 mixtures will be performed. The DNS data will be analyzed to extend the present CO model to adequately consider the effects of H2 addition. The full model will be used in the LES of two model combustion chambers and validated with experimental data. Funding for this project is requested jointly from the DFG and the FVV. While the two proposed work packages address pollutant formation in different environments, strong connections are given by the embedding of the work packages in the project support provided by industrial partners of the FVV. Similar modeling approaches and research methodologies will be used for the prediction of CO and soot, so that the joint model development can lead to a generic description of pollutant formation.

• DFG Programme: Research Grants