Details

Autor(en) / Beteiligte

• Göktolga, M. Ugur
• van Oijen, Jeroen A.
• de Goey, L. Philip H.

Titel

3D DNS of MILD combustion: A detailed analysis of heat loss effects, preferential diffusion, and flame formation mechanisms

Ist Teil von

• Fuel (Guildford), 2015-11, Vol.159, p.784-795

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2015

Link zum Volltext

Quelle

ScienceDirect Journals (5 years ago - present)

Beschreibungen/Notizen

• Moderate or intense low oxygen dilution (MILD) combustion is a relatively new technology which combines low emissions with high efficiency. As the name suggests, it requires high degrees of dilution in addition to preheating of the reactants using the combustion products. It has been applied to industrial burners for some time, but the complex physical mechanisms are yet to be resolved to extend the application to other areas. In this study, our aim is to analyze MILD combustion conditions to reveal the mentioned physical phenomena and their interactions. To this end, direct numerical simulations (DNS) in the form of autoigniting mixing layers are conducted, and the results are thoroughly analyzed. Conditions used in the simulations are taken from the jet in hot coflow experiments, which are designed to mimic MILD conditions. Detailed chemistry and transport models are employed in the numerical tools to fully understand the interactions of turbulence, molecular diffusion and chemical reactions. In addition, temperature variations due to heat loss effects in the experiments are taken into account. We have found that the heat loss and preferential diffusion effects are crucial in predicting not only the ignition delay, but also the flame structures and heat release rates. In addition, it is found that the flame formation is initiated by autoignition with different ignition delays along the most reactive mixture fraction, instead of a flame propagation following an initial autoignition spot. The findings of this study will broaden the knowledge on MILD combustion, and provide useful insight in developing reduced turbulence and chemistry models in the future.