Details

Autor(en) / Beteiligte

• Niemietz, Kai
• Berger, Lukas
• Huth, Michael
• Attili, Antonio
• Pitsch, Heinz

Titel

Direct numerical simulation of flame-wall interaction at gas turbine relevant conditions

Ist Teil von

• Proceedings of the Combustion Institute, 2023, Vol.39 (2), p.2209-2218

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• A direct numerical simulation (DNS) with finite rate chemistry was performed to evaluate the main influences on carbon monoxide (CO) emissions in gas turbine combustion. A lean methane/air mixture is burned in fully turbulent jet flames in a domain enclosed by isothermal walls. The formation of CO is found to be affected by the mean strain rate of the turbulent flow, the flame-wall interaction (FWI), and the interactions of the flame with the recirculation zones of the flow. The CO production and consumption in the turbulent flame differ strongly from the reaction rates in a freely propagating flame. In the upstream part of the domain, the mean strain rate of the turbulent flow mainly affects the CO formation, while wall heat loss influences the CO oxidation process towards the end of the domain, where the strain rate decreases. In an optimal estimator analysis, the relevant parameters that dominate the formation and consumption of CO are identified as the local CO mass fraction YCO, the wall heat loss, described by the enthalpy defect Δh, and the mass fraction of the OH radical YOH. The heat loss is particularly influential close to the wall while the effects far from the wall are negligible. Using the local CO mass fraction as parameter describes the late-stage oxidation of CO well in the entire domain. In particular, YCO should not be neglected at the wall. YOH is well suited to describe the processes involved in CO oxidation, as it both parameterizes the turbulent strain and is the main reaction partner for CO oxidation. The combination of YCO and Δh was able to improve the domain-averaged irreducible error by almost half compared to only a progress variable. Adding YOH to the parameter set further reduced the error to 25% of the original error.