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The release of inorganic elements, especially K, Cl, and S, can cause severe damage to biomass conversion devices, such as slagging, fouling, or corrosion. A predictive model for the release of K-Cl-S elements can be used to enhance the design and operating conditions of biomass conversion devices. In this study, a detailed model is developed that includes 12 solid species and 13 reactions, which can represent the main pathways of the release of K-Cl-S from the particle. The model is coupled to a particle model to predict the release of potassium from different types of biomass at various operating conditions. First, the types and solubility of the potassium after pyrolysis and combustion at different temperatures are compared with the experimental data from the literature. The model predictions of the H 2 O-soluble, NH 4 AC-soluble, stable, and total potassium are comparable to the experimental data. Second, the K, Cl, and S in two types of biomass with high and low Si content are studied and compared with the experimental data. The model is used to explain different stages of potassium, sulfur, and chlorine release, which were observed in the experiments. Finally, the concentration of gas-phase potassium-containing species, i.e., atomic K, KCl, and KOH, downstream of burning biomass particles at different temperatures are investigated and compared with experimental measurement. The model can capture the release behavior of these species at different temperatures with good accuracy. The model results are summarized to create a clearer picture of the pathways of K-Cl-S-release from biomass and their interactions with other ash elements. [ABSTRACT FROM AUTHOR]

In this paper, a novel multi-region Eulerian model is presented to study the conversion of thermally thick biomass particles. In the present model, the particle and the surrounding fluid are treated as two separate regions that are coupled through an interface. There are some benefits for using a multi-region approach, including a more realistic radiation modeling, flexibility to define the flow boundary conditions at the surface of the particle, and also the possibility to use different governing equations for each region. Furthermore, the multi-region approach provides a solution to the stiff problem of coupling the particle to the surrounding fluid which can be used to significantly reduce the computational cost. In the current model, sub-models for drying, pyrolysis, gasification, combustion, and shrinkage are included. The local effect of shrinkage is considered through porosity change and the global effect of shrinkage is modeled using a dynamic mesh approach. The particle surface and center temperature and particle mass loss during pyrolysis and combustion are compared to different sets of experimental data. The model is used to study the shrinkage and anisotropic heat transfer on particle conversion, and also the pyrolysis in cases with and without the gas phase reactions. [ABSTRACT FROM AUTHOR]

A three-dimensional reactive multi-phase particle-in-cell (MP-PIC) model is employed to investigate biomass combustion and gasification in fluidized bed furnaces. The MP-PIC model considered here is based on a coarse grain method (CGM) which clusters fuel and sand particles into parcels. CGM is computationally efficient, however, it can cause numerical instability if the clustered parcels are passing through small computational cells, resulting in over-loading of solid particles in the cells. To overcome this problem, in this study, a distribution kernel method (DKM) is proposed and implemented in an open-source CFD code, OpenFOAM. In DKM, a redistribution procedure is employed to spread the solid volume and source terms of the particles in the parcel to the domain in which the particles are clustered. The numerical stiffness problem caused by the CGM clustering can be remedied by this method. Validation of the model was performed using data from different lab-scale reactors. The model was shown to be able to capture the transient heat transfer process in a lab-scale bubbling fluidized bed reactor under varying fluidization velocities and loads of sand. Then, the model was used to study the combustion/gasification process in a bubbling fluidized bed reactor under varying ambient temperatures, equivalent air ratios, and steam-to-biomass ratios. The performance of DKM was shown to improve the accuracy and the robustness of the model. [ABSTRACT FROM AUTHOR]