Analysis of convective drying in particles of pine wood chips for bioenergy

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Abstract

This research aimed to analyze and adjust the theoretical equations used in mass transfer models to estimate the drying rate in pine wood chips, considering different chip column heights and particle sizes. For this purpose, an experimental biomass dryer was designed and built, which allowed, under different levels of minimum and maximum capacity, to establish a series of drying treatments evaluated under different conditions. One of the main contributions of this work lies in the novel equations that allow, from air parameters, to accurately calculate the drying rate and, therefore, to estimate the time required for complete drying of forest biomass. This is achieved through regression models applied in an innovative way, offering new predictive tools and establishing a clear and replicable procedure for its application in practice. The results obtained in this study demonstrate that wood chip drying is not a linear process; the drying rate decreases over time and is affected by factors such as particle size and operating conditions such as air speed and temperature. The drying process exhibited a relative drying rate ranging from 0.0380 g/s·kg in small particles (at low air velocities and temperatures) to 0.0695 g/s·kg in large particles (at high air velocities and temperatures). The absolute drying rate varied between 0.0034 g/s in small particles and 0.0057 g/s in large particles. The findings revealed that the models explained between 58% and 83% of the variability observed in the treatments. Statement of Novelty. This research arises from the need to more accurately predict the drying time of pine wood chips, a fundamental aspect for optimizing biofuel production. Currently, experimental drying models using hot airflows have limitations, as they are designed for fixed environmental conditions of temperature, flow rate, and relative humidity, making their application challenging in environments with variations in these variables. To overcome these limitations, some studies have proposed models based on the analysis of mass and heat transfer phenomena to predict the drying rate. However, the number of influencing factors still causes theoretical data to not precisely match experimental data. This study proposes complementing mass transfer equation-based models adapted to kinetic models with experimental data fitting models, significantly improving prediction accuracy. Since drying processes depend on the Biot number in mass transfer and the Biot number in heat transfer, which assess the relationship between diffusion and convection in each subsystem based on the size of the solids undergoing drying, this work introduces differentiated equations for different size ranges of wood chips. The main contribution lies in integrating theoretical data into equations that more accurately reflect experimental results, providing an innovative tool for both the scientific and industrial communities. This approach not only allows for adjusting production times based on real environmental conditions but also contributes to improving energy efficiency and sustainability in the bioenergy industry, ensuring that biomass reaches the appropriate moisture level for use as biofuel.

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