Coupling a stochastic soot population balance to gas-phase chemistry using operator splitting
Coupling a stochastic soot population balance to gas-phase chemistry using operator splitting
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DOI：
10.1016/j.combustflame.2006.10.007
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发表时间：
2007-02
影响因子：
4.4
通讯作者：
M. Celnik;R. Patterson;M. Kraft;W. Wagner
中科院分区：
文献类型：
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作者：
M. Celnik;R. Patterson;M. Kraft;W. Wagner
研究了将随机碳烟算法与确定性气相化学求解器相耦合的可行性。二阶分裂技术被用来解耦颗粒群和气相，以解决。一个数值收敛性研究表明收敛与分裂步长和颗粒计数的间歇式反应器和一个完全搅拌反应器。模拟结果与活塞流反应器（PFR）的实验数据，并进行了比较，一个完美的搅拌反应器的时刻模拟的方法。耦合的烟尘和化学求解收敛两个系统，但是，数值不稳定性提出了重大挑战的PSR的情况下。与PFR的实验数据的比较表明，良好的协议的烟尘质量和合理的协议的粒度分布。两种不同的烟灰颗粒模型被用来模拟PFR：一个球形颗粒模型和一个表面体积模型，需要考虑一些颗粒形状。两种模型的结果进行了比较。此外，随机碳烟求解器被用来跟踪的PFR中的单个碳烟颗粒的C/H比的演变的第一次。
The feasibility of coupling a stochastic soot algorithm to a deterministic gas-phase chemistry solver is investigated for homogeneous combusting systems. A second-order splitting technique was used to decouple the particle population and gas phase in order to solve. A numerical convergence study is presented that demonstrates convergence with splitting step size and particle count for a batch reactor and a perfectly stirred reactor. Simulation results are presented alongside experimental data for a plug flow reactor (PFR) and are compared to a method of moments simulation of a perfectly stirred reactor. Coupling of the soot and chemistry solvers is shown to converge for both systems; however, numerical instabilities present significant challenges in the PSR case. Comparison with the experimental data for a PFR showed good agreement of the soot mass and reasonable agreement of the particle size distribution. Two different soot particle models were used to simulate the PFR: a spherical particle model and a surface–volume model that takes some account of particle shape. The results for the two models are compared. Additionally, the stochastic soot solver is used to track the evolution of the C/H ratio of individual soot particles in the PFR for the first time.