A research collaboration of national laboratories for the U.S. DOE Bioenergy Technologies Office
Accurate modeling of intra-particle heat and mass transfer is important for simulating biomass pyrolysis, because resulting product yield and composition are known to be strong functions of the heating rate and internal secondary reactions. Developing such models is a challenge because biomass particles are typically anisotropic and contain complex pores and lumens that can vary widely between species. The difficulty is further increased when simulating realistic biomass feedstocks, which can also be highly variable in size and composition.
Many particle models assume over-simplified geometries that neglect important structural characteristics of biomass. These characteristics, including particle morphology and internal microstructure, can vary substantially between species of origin and particle size reduction methods. NREL has developed methods to construct improved biomass particles based on direct microscopic measurements of particle morphology and microstructural dimensions. The resultant models serve as the geometry for simulations of transport phenomena coupled to chemical transformation. These simulations are used to predict particle heat-up times and extent of conversion during fast pyrolysis as a function of size, shape, and species.
Many current biomass pyrolysis models approximate intra-particle heat and mass transport using 1-D, transient differential energy and mass balances that do not consider anisotropy or inhomogeneity. Also, particle geometry is commonly specified in terms of ideal shapes such as cubes, cylinders, or spheres, which do not readily lend themselves to inclusion of complex spatial heterogeneity. Although a few multi-dimensional (2-D and 3-D) intra-particle transport models have been proposed, their ability to account for the impact of directional anisotropy and spatial heterogeneity during pyrolysis is still an active area of development.
In collaboration with NREL, ORNL is developing an improved low- order model for biomass particles as they undergo rapid heating and devolatilization typical of fast pyrolysis conditions for bio-oil production. Using results from complex 3-D particle models, we demonstrate how it is possible to construct reasonably accurate coarse-grained particle models that approximate the overall behaviour of high resolution models for rapid, low-cost simulations. Specific recommendations will be developed regarding additional experimental measurements that are needed to validate and further refine pyrolysis models. When incorporated into a reactor-level model, the improved intra-particle model will enhance the predication of bio-oil yield associated with operating parameters for both experimental-scale and commercial-scale reactors.
In FY14, INL measured apparent specific heat and thermal conductivity of clean pine and poplar wood chips at 25 °C, 300°C, and 500 °C under steady-state conditions. Specific heat measurements were also conducted over the same temperature range at a heating rate of 20°C/min. Mettler-Toledo provided corresponding preliminary data using a flash differential scanning calorimeter (DSC 1) with particles weighing approximately 100 μg at rates of approximately 200°C/sec. The purpose of these measurements is to provide the thermal properties needed to accurately predict heat transfer in woody particles during fast pyrolysis reactions.
In FY15, INL is investigating the need to measure diffusion coefficients for H2O, CO and CO2 for woody materials as they are heated from room temperature to 500°C. INL will also perform material grinding experiments and characterizations of ground materials to determine the distributions of size and shape characteristics of representative woody materials that are fed into fast pyrolysis conversion reactors.
The CCPC is an enabling project in the ChemCatBio consortium
ChemCatBio is part of DOE’s Energy Materials Network
Feedstock-Conversion Interface Consortium
Bioprocessing Separations Consortium
U.S. DOE Bioenergy Technologies Office
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