Coupling a stochastic soot population balance to gas-phase chemistry using operator splitting
Autor: | Markus Kraft, Robert I. A. Patterson, Wolfgang Wagner, Matthew S. Celnik |
---|---|
Rok vydání: | 2007 |
Předmět: |
education.field_of_study
General Chemical Engineering Numerical analysis Monte Carlo method Population General Physics and Astronomy Energy Engineering and Power Technology General Chemistry Mechanics medicine.disease_cause Soot Fuel Technology Strang splitting medicine Particle Statistical physics Particle size Plug flow reactor model education |
Zdroj: | Combustion and Flame. 148:158-176 |
ISSN: | 0010-2180 |
DOI: | 10.1016/j.combustflame.2006.10.007 |
Popis: | 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. |
Databáze: | OpenAIRE |
Externí odkaz: |