Computational Modeling of Biomass Fast Pyrolysis in Fluidized Beds with Eulerian Multifluid Approach
Cesar M. Venier,
Erick Torres,
Gastón G. Fouga,
Rosa A. Rodriguez,
Germán Mazza,
Andres Reyes Urrutia
Affiliations
Cesar M. Venier
Instituto de Física de Rosario, IFIR (CONICET-Universidad Nacional de Rosario), Santa Fe S2000, Argentina
Erick Torres
Instituto de Ingeniería Química—Facultad de Ingeniería, Universidad Nacional de San Juan-Grupo Vinculado al PROBIEN (CONICET-UNCo), San Juan J5402, Argentina
Gastón G. Fouga
Departamento de Fisicoquímica y Control de Calidad, Complejo Tecnológico Pilcaniyeu, CAB-CNEA (CONICET), Av. Exequiel Bustillos, km 4.5, Bariloche R8412, Argentina
Rosa A. Rodriguez
Instituto de Ingeniería Química—Facultad de Ingeniería, Universidad Nacional de San Juan-Grupo Vinculado al PROBIEN (CONICET-UNCo), San Juan J5402, Argentina
Germán Mazza
Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas, PROBIEN (CONICET-Universidad Nacional del Comahue), Neuquén Q8300, Argentina
Andres Reyes Urrutia
Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas, PROBIEN (CONICET-Universidad Nacional del Comahue), Neuquén Q8300, Argentina
This study investigated the fast pyrolysis of biomass in fluidized-bed reactors using computational fluid dynamics (CFD) with an Eulerian multifluid approach. A detailed analysis was conducted on the influence of various modeling parameters, including hydrodynamic models, heat transfer correlations, and chemical kinetics, on the product yield. The simulation framework integrated 2D and 3D geometrical setups, with numerical experiments performed using OpenFOAM v11 and ANSYS Fluent v18.1 for cross-validation. While yield predictions exhibited limited sensitivity to drag and thermal models (with differences of less than 3% across configurations and computational codes), the results underline the paramount role of chemical kinetics in determining the distribution of bio-oil (TAR), biochar (CHAR), and syngas (GAS). Simplified kinetic schemes consistently underestimated TAR yields by up to 20% and overestimated CHAR and GAS yields compared to experimental data (which is shown for different biomass compositions and different operating conditions) and can be significantly improved by redefining the reaction scheme. Refined kinetic parameters improved TAR yield predictions to within 5% of experimental values while reducing discrepancies in GAS and CHAR outputs. These findings underscore the necessity of precise kinetic modeling to enhance the predictive accuracy of pyrolysis simulations.