Flammensynthese kleinster Partikel: Modellierungsstrategien für die Partikelproduktion in turbulenten, reaktiven Strömungen

• Applicant: Professor Dr. Andreas Kronenburg
• Subject Area: Energy Process Engineering
• Term: from 2011 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 200341289

• Final Report Year: 2017

Final Report Abstract

The flame synthesis of nanoparticles is a typical multi-scale process: the relatively large scales of the turbulent flow field interact with the relatively small scales that dominate particle nucleation and growth. These small scales are usually not resolved on the computational grid and need modelling. In this work, we have proposed a sparse-Lagrangian multiple mapping conditioning (MMC) model that captures the interactions between turbulence, chemical reactions and particle dynamics. We use direct numerical simulations of a temporally evolving reacting shear layer to validate the approach. The fuel stream consists of nitrogen doped with silane, the oxidizer stream consists of hot products from a lean hydrogen-air flame. The Lagrangian particle solutions approximate the DNS solutions very well indicating a correct closure of all processes at all scales. To achieve this excellent agreement the modelling of the turbulent mixing time scale of the particles needed to be revisited. A new model for the mixing time scale is suggested and thorough analyses of the influence of modelling parameters (particle distance, particle localization in composition space) and of numerical parameters. In particular the study on the numerical convergence for varying Lagrangian particle numbers has addressed critical issues that had been associated with MMC due to the very low Lagrangian particle number. We have demonstrated (1) consistency and (2) feasibility of MMC to predict turbulent, reacting single and two phase flows. In a last step, we have coupled MMC with large-eddy simulations (LES) of the flow field and the Lagrangian particle solution acts as a sub-grid closure for the modelling of turbulencechemistry interactions. MMC-LES provides accurate appoximations of the DNS solution at a fraction of the computational cost: while DNS of particle synthesis require 40,000 CPUh, MMC-LES of the same setup can easily be realized on a single core at a cost of 5 CPUh.

Publications

• “Assessment of mixing time scales for a sparse particle method”, Combust. Flame, (2017)
  S. Vo, O. T. Stein, A. Kronenburg and M. J. Cleary
  
• Analysis of LES-MMC modelling using DNS of a reacting mixing layer”, 8th International Seminar on Flame Structure, May 9-10 2014, Berlin, Germany
  S. Vo, A. Kronenburg, O.T. Stein, Y. Ge, A.Y. Klimenko and M.J. Cleary
  
• “Analysis of MMC mixing model using DNS of an evolving double shear layer with extinction and reignition”, 7th European Combustion Meeting, Mar 30 - Apr 2 2015, Budapest, Hungary
  S. Vo, A. Kronenburg, O. T. Stein and M. J. Cleary
  
• (2017): Multiple mapping conditioning for silica nanoparticle nucleation in turbulent flows. In: Proceedings of the Combustion Institute 36 (1), S. 1089–1097
  S. Vo, A. Kronenburg, O. T. Stein and M. J. Cleary
  
• “Direct numerical simulation of non-premixed syngas combustion using OpenFOAM”, in High Performance Computing in Science and Engineering ’16 ; Eds. W.E. Nagel, D.B. Kröner, M.M. Resch, Springer Verlag (2017), 245 – 255 (ISBN: 978-3-319-47065-8)
  S. Vo, A. Kronenburg, O. T. Stein and E. R. Hawkes
  
• “Multiple mapping conditioning for silica nanoparticle nucleation in turbulent flows”, Proc. Combust. Inst., 36:1089 – 1097 (2017)
  S. Vo, A. Kronenburg, O. T. Stein and M. J. Cleary