Sparse particle methods for turbulent premixed combustion

• Applicant: Professor Dr. Andreas Kronenburg
• Subject Area: Energy Process Engineering
• Term: from 2017 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 393542303

Novel burner concepts are primarily designed for lean premixed combustion. To guarantee ignition and operational safety, some local fuel stratification is needed, however, leading to inhomogeneities of the fuel-air mixture. The additional requirements of higher throughput and a size reduction of the combustion chambers may increase the turbulence levels such that the predominant flame regime shifts from the flamelet to the thin-flame regime. Current combustion models are usually based on the flamelet assumption, and no current model can reliably predict fuel stratification and deviations from the flamelet regime.The proposed study will develop a particle based Monte Carlo method for the modelling of turbulent premixed flames. Every Monte Carlo (PDF) particle represents an instantaneous, local solution of a fluid element. These instantaneous solutions then allow for the approximation of the joint probability density function (PDF) of the chemical composition of the gas phase and thus of the inner structure of the premixed flame. The conservation equations for the velocity field are solved in a Eulerian framework with the aid of large-eddy simulations (LES).The modelling of molecular and turbulent diffusion pose the major challenge: the application of standard mixing models to premixed combustion leads to uncontrolled and unphysical mixing across the flame front that hinder the accurate prediction of the flame structure and even of the burning velocity. The novelty of the proposed work is the use of a sparse particle method for the computation of the gas phase composition PDF. Conventional particle methods require between 20 and 50 particles per LES cell and their numerical solution can be extremely costly. The particle number can be lowered to less than 1 particle per 10 LES cells when using sparse methods, and simulation times can be significantly reduced. This is realized by conditioning of the mixing operator on a reference field. And it is this reference field that can be used to model diffusion as a multistep process that prevents mixing across the flame front and ensures a continuous increase of particle temperature in the preheat zone and limits particle ignition and heat release to the reaction zone.First, direct numerical simulations (DNS) of simple, statistically one-dimensional flames will aid the development of new closures. Then, the DNS configuration will be extended to include fuel stratification. In a final step, the new closures will be applied to real laboratory flames and will be validated with the aid of available experimental data.

• DFG Programme: Research Grants