(30b) Combining High and Low-Order Computational Models to Simulate Biomass Fast Pyrolysis Reactors

Fast pyrolysis is a leading candidate technology for the thermochemical conversion of solid biomass into liquid bio-oils which can be used as feedstocks for producing biofuels and high-value chemicals. Bio-oils are commonly generated in fluidized, circulating, or entrained flow reactors in which biomass particles rapidly devolatilize in the absence of oxygen into mixtures of light gases, condensable bio-oil vapors, and char. To maximize bio-oil yields, the reactors typically operate at temperatures near 500°C and must maintain particle residence times in the range of 2-5 seconds and gas residence times less than 1 second. Deviations from these conditions can result in significant production and quality penalties, therefore optimal reactor design and control become crucial to achieving commercially viable bio-oil production.

In this presentation, we describe preliminary results produced with a hybrid modeling approach for simulating laboratory-scale biomass pyrolysis reactors. By exploiting the fact that the biomass solids loadings and heats of reaction are both relatively low, we can separate the complex gas-particle hydrodynamics from particle-scale and homogeneous gas-phase chemical reaction kinetics and thereby greatly accelerate the simulation process. Our approach is based on initially modeling the detailed particle-gas hydrodynamics in MFiX using the discrete element method (DEM) and the two-fluid model (TFM) to determine the residence time distributions (RTDs) of the different size biomass particles in the reaction zone. We then use the resulting particle RTDs in low-order reactor models written in Python to account for particle-scale and gas-phase reaction kinetics to estimate the trends in net bio-oil pyrolysis yield for a range of reactor conditions.