Abstract
Biomass gasification offers a significant potential to close the loop of agriculture and many other activities that produce biomass residues. However, the presence of tars and impurities, such as soot, in the gasification products is still a major bottleneck causing operational problems, particularly blocking or fouling of equipment and low syngas quality. Numerical modelling is a very attractive solution to enhance the understanding of the physical and chemical phenomena occurring in gasifiers and thereby to overcome these barriers. In addition, understanding the biomass gasification fundamentals in laboratory-scale devices, such as drop tube furnaces (DTF), is crucial to evaluate its relevance for industrial applications. The main objective of this study is to develop a model able to predict soot formation during the gasification of biomass in a DTF. The model developed is based on a kinetic-diffusion approach and was implemented in Python using the Cantera reaction kinetics library. The model is validated against experimental data that assessed the effect of the temperature and steam to biomass (S/B) ratio on char and soot yields and syngas composition during the gasification of wheat straw in the DTF. Overall, the model developed captures with a rather good accuracy the evolution of the char yields, but with a less accuracy the evolution of the soot yields and syngas composition with the temperature and S/B ratio.
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