Development of a solid-gas coupled model for thermally thick biomass combustion in packed beds

Abstract

The aim of this research is to model the moving grate combustion process by Computational Fluid Dynamics (CFD) method by OpenFOAM software. Kinetic data for heterogeneous reactions, specific to local fuel types is essential. Therefore, pyrolysis kinetics of Rubber and Gliricidia was evaluated by two methods; the sequential approach for Kissinger method and Miura and Maki approach for Ditributed Activation Energy Model (DAEM). The activation energy values obtained by the sequential spproach for Kissinger method are 107.9 kJmol-1 for Gliricidia and 83.44 kJmol-1 for Rubber wood. Obtained activation energy by Miura and Maki approach for DAEM, varies between 190.57 kJmol-1 and 230.58 kJmol-1 for Gliricidia and between 111.52 kJmol-1 and 179.07 kJmol-1 for Rubber wood. A CFD model was developed which describes the wood combustion in fixed grate type packed bed furnaces. Linear rate of mass loss observed in batch type simulations can be used to describe the steady state burning characteristics of a continuously operated furnace which has a feeding rate equal to burning rate. This mass loss rate was used to evaluate Equivalence Ratio (ER) variation for different particle sizes of wood. A sensitivity analysis was conducted to find the effect of moisture content and particle size on ER. It was found that moisture content of wood has more significant effect on ER than the particle size. The optimum equivalence ratio was studied based on the maximum outlet gas temperature with minimum CO fraction for different particle sizes of wood. The optimum ER values obtained were 0.28 for 25 mm sized particles, 0.13 for 38 mm sized particles and 0.18 for 63 mm sized particles. The model was elaborated to simulate wood combustion in moving grate type furnaces. This heterogeneous model developed within Eulerian framework, includes the grate movement through boundary conditions, which can solve both bed and free board region simultaneously.