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The Effect of Preferential Diffusion on the Soot Initiation Process in Ethylene Diffusion Flames
(2011)
"Reduction of Complex Fuel Chemistry for Simulation of Combustion in a PSR-PFR reactor sequence"
(2001)
Biomass devolatilization and incineration in grate-fired plants are characterized by heterogeneous fuel mixtures, often incompletely mixed, dynamical processes in the fuel bed and on the particle scale, as well as heterogeneous and homogeneous chemistry. This makes modeling using detailed kinetics favorable but computationally expensive. Therefore, a computationally efficient model based on zero-dimensional stochastic reactors and reduced chemistry schemes, consisting of 83 gas-phase species and 18 species for surface reactions, is developed. Each reactor is enabled to account for the three phases: the solid phase, pore gas surrounding the solid, and the bulk gas. The stochastic reactors are connected to build a reactor network that represents the fuel bed in grate-fired furnaces. The use of stochastic reactors allows us to account for incompletely mixed fuel feeds, distributions of local temperature and local equivalence ratio within each reactor and the fuel bed. This allows us to predict the released gases and emission precursors more accurately than if a homogeneous reactor network approach was employed. The model approach is demonstrated by predicting pyrolysis conditions and two fuel beds of grate-fired plants from the literature. The developed approach
can predict global operating parameters, such as the fuel bed length, species release to the freeboard, and species distributions within
the fuel bed to a high degree of accuracy when compared to experiments.
Abstract In this paper, a partially stirred stochastic reactor model is presented as an alternative for the modeling of biomass pyrolysis and gasification. Instead of solving transport equations in all spatial dimensions as in CFD simulations, the description of state variables and mixing processes is based on a probability density function, making this approach computationally efficient. The virtual stochastic particles, an ensemble of flow elements consisting of porous solid biomass particles and surrounding gas, mimic the turbulent exchange of heat and mass in practical systems without the computationally expensive resolution of spatial dimensions. Each stochastic particle includes solid phase, pore gas and bulk gas interaction. The reactor model is coupled with a chemical mechanism
for both surface and gas phase reactions. A Monte Carlo algorithm with operator splitting …