Yonduck "James" Sung, Department of Mechanical Engineering, University of Texas at Austin, 210 E. 24th street, Bldg WRW, 305, Austin, TX 78712, Venkatramanan Raman, Department of Aerospace Engineering & Engineering Mechanics, University of Texas at Austin, 210 E. 24th street, Bldg WRW, 305, Austin, TX 78712, and R. O. Fox, Department of Chemical & Biological Engineering, Iowa State University, 2114 Sweeney Hall, Ames, IA 50011-2230.
Gas-phase combustion based particulate synthesis provides an attractive route for large-scale production of practically relevant nanoparticles. Here, precursors are introduced in a pre-existing flame leading to the formation of metal-oxides in the high-temperature environment. However, the size and number distribution of the particles are critically dependent on the turbulent combustion process. If this multiscale interaction can be understood and modeled accurately, viable fast-throughput processes could be designed. As a first step towards this goal, a novel direct numerical simulation approach is developed here. The gas-phase turbulent combustion is fully resolved by the computational grid. The nanoparticle population evolution is tracked using the direct quadrature method of moments (DQMOM) approach. A planar reacting jet configuration is used to study the effect of gas-phase combustion on the particle evolution process. The rate of particle growth, sintering, and agglomeration are very sensitive to the gas-phase temperature and thermochemical composition. In particular, the history of gas-phase conditions encountered by the population ultimately determines the outlet size distribution. In this context, the DNS database is used to identify the important modeling hurdles. Further, specific numerical issues relevant to solving the population balance equation in this framework are discussed.