NOx Emission Modelling for Lean Premixed Industrial Combustors With a Diffusion Pilot Burner

Autor: Thomas Kaiser, Christian Oliver Paschereit, Jakob G. R. von Saldern, Jan Paul Beuth, Johann Moritz Reumschüssel, Franklin Marie Genin, Kilian Oberleithner, Thoralf G. Reichel, Bernhard Ćosić
Rok vydání: 2021
Předmět:
Zdroj: Volume 3A: Combustion, Fuels, and Emissions.
DOI: 10.1115/gt2021-59071
Popis: In gas turbine combustion systems, the reduction of emissions of harmful combustion by-products is a main development goal. This study provides a methodology to model NOX emissions effectively for varying levels of pilot fuel flows at different operational points. It combines one-dimensional flame simulations using detailed chemistry with a stochastic approach for equivalence ratio fluctuations to account for the effect of fuel-air unmixedness. This split allows for computationally fast variations of the gas inlet condition and the consideration of different shares of pilot gas. The generation of emissions is split into a share of prompt formation at the flame front and a slower formation mechanism, occurring within the combustion products in the post flame region. The influence of unmixedness of the fuel-air mixture on both effects is taken into consideration by means of probability density functions (PDFs) of the equivalence ratio. These are modeled on the basis of sampled values from Large Eddy Simulations at the flame front and adapted for different shares of pilot gas. It is shown that with a superposition of Gaussian PDFs the equivalence ratio distribution at the flame front resulting from the main gas supply and the pilot share can be well approximated. Measurement data from experiments in atmospheric conditions as well as emission measurements from high pressure tests are used to evaluate the model. Good agreement is found for atmospheric data, allowing for explanations on the effect of pilot fuel ratio on emissions. For elevated pressure, only qualitative trends could be reproduced. Hypotheses to explain this deviation are made that motivate further research.
Databáze: OpenAIRE