(82c) Global Kinetics for the Simulation of Biomass Pyrolysis in Fluidized Bed Reactors

Pepiot, P., Cornell University
Malhotra, K., Cornell University
Nimlos, M., National Renewable Energy Laboratory
Ciesielski, P. N., National Renewable Energy Laboratory
Grout, R., National Renewable Energy Lab

Accounting adequately for the chemical processes and their interactions with the surrounding flow dynamics is an essential step toward predictive Computational Fluid Dynamic (CFD) simulations of biomass-to-biofuel thermochemical conversion. The direct implementation of detailed kinetic mechanisms, involving a large number of chemical species and elementary reactions, is usually proscribed due to limited available computational resources. While numerous chemistry reduction techniques have been developed to generate reduced-order kinetic models from more detailed kinetic schemes, these techniques are unable to handle the complex, multiphasic nature of biomass chemistry, and in general, cannot achieve the very high level of reduction required by most CFD tools. A systematic strategy is presented here to reduce a given detailed kinetic model into a global model that will: (i) contain many fewer reaction steps, (ii) use lumped variables that combine species of similar chemical nature, and (iii) maintain the predictive capabilities of the detailed mechanism for the quantities of interest. The approach is demonstrated in the context of biomass pyrolysis in fluidized bed reactors. Partially stirred reactor (PaSR) models are used in conjunction with existing detailed chemical kinetic mechanisms for both solid and gas phase chemistry, to generate a database of compositions likely to occur in an actual reactor. From the analysis of this database, representative lumped species, and an appropriate set of global reactions and corresponding kinetic rates are identified automatically. Validation is performed in various configurations, and the resulting global model is integrated into a Lagrangian particle tracking tool recently developed for the large-scale simulation of reactive granular flows.