A numerical model approach to predict moisture absorption in densified solid biomass during storage

Abstract

Bioenergy from wood pellets has aggressively grown due to its potential to reduce fossil fuel consumption and carbon emissions. Wood pellets demand is on rise as a result a large volume of pellets are manufactured and stored before consumption. Wood pellets are inherently hygroscopic and readily absorb moisture during storage. Increased moisture content (M) reduces the heating value, energy efficiency and mechanical durability of wood pellets. Although the moisture absorption behavior of wood pellets is well documented, no predictive model is available to simulate the moisture content in wood pellets. In this research, the kinetics of moisture absorption in wood pellets was analyzed using Fick’s law of diffusion. A numerical model was developed to predict the moisture content in wood pellets for different storage conditions. The moisture absorption by wood pellets conditioned in a humidity chamber under two temperatures and two relative humidity’s (RHs) was studied over a period of 45 days. The moisture absorption pattern in wood pellets followed Fick’s law model with a linear initial part and an equilibrium plateau. Considering the principles of moisture absorption in porous media, an exponential equation modeled the moisture absorption in wood pellets and a good agreement was observed between the numerical model and the experimental data. The high values of coefficient of determination (R2) and low values of root mean square demonstrated the suitability of the proposed numerical model to predict moisture content in wood pellets. This model can help the densified biomass processors to estimate the moisture uptake during storage conditions.