The overarching goal of the study presented in this dissertation is to develop a predictive computational model that can describe the detailed chemical and physical processes associated with pyrolysis, heat transfer and combustion for solid waste in a fixed bed gasifier. The work is applicable to optimization and prediction of the synthetic gas composition of solid waste gasifier operations. The dissertation is comprised of two main parts.

In the first part, a predictive three-dimensional model for municipal solid waste gasification process is developed. The multiphase flow is described by a porous flow model using the SIMPLE algorithm with momentum interpolation. The governing equations are transformed into a generalized coordinate system to be applicable to realistic reactor geometry. A simplified global reaction mechanism is adapted for the gas-phase chemical reactions inside the gasifier. The pyrolysis process is described by a phenomenological Lagrangian pyrolysis model to determine the local porosity distribution and the corresponding pyrolysis rate of the waste. Computational results show three-dimensional distribution of the flow field, temperature, species concentration, porosity and the stack morphology under different parametric conditions. The effects of the inlet temperature and the feeding rate on the waste stack shape are studied. The results demonstrate that the model can properly capture the essential physical and chemical processes in the gasifier and thus can be used as a predictive simulation tool.

In the second part, the Lagrangian pyrolysis model is extended to consider a multiple characteristic diameter (MCD) pyrolysis submodel in order to independently determine the rate of the local devolatilization, drying and charring processes associated with realistic biomass fuels. The porosity distribution is determined by introducing the local characteristic diameter of the virtual solid spheres representing the biomass fuel. Global homogeneous and heterogeneous reactions were adapted for the chemical reactions inside the gasifier. Synthetic gas compositions from model prediction are validated experiments conducted by Korean Institute of Energy Research (KIER) with good agreements. Model predictions are also compared with the results calculated by the equilibrium model in order to demonstrate that the proposed model improves the predictive capability of the complex nonequilibrium processes inside the gasifier.