Numerical simulation of soot generation during biomass gasification with a moment projection method

Artikel i vetenskaplig tidskrift, 2026

Syngas produced from biomass gasification has significant potential as a biofuel resource. The purity of syngas is important for its subsequent catalytic conversions. However, high-temperature gasification is usually accompanied by the generation of nano-sized soot particles that can easily deactivate catalysts. Therefore, exploring the underlying physics of soot formation, to enable its control and reduction, is a key issue in highly efficient biomass gasification. The intrinsic multi-scale characteristics of soot generation pose a great challenge for numerical simulations. In this paper, a novel moment projection method, which solves the closure problem encountered by traditional moment methods under oxidation conditions, is integrated with an Eulerian-Lagrangian gasification model to study the behavior of biomass soot generation. The new method is comprehensively validated with existing pyrolysis and gasification experiments, and the performance is also compared with that of empirical models. The prediction accuracy of the moment projection method is systematically assessed in the pyrolysis of cellulose and softwood lignin under 800–1300°C. A significant improvement is achieved as compared with a two-equation soot formation model. Besides, the soot particle size distribution is also well captured in the simulation. The new algorithm is then utilized to study the soot generation under different gasification temperatures and steam/biomass ratios. Simulation results demonstrate the superior ability of the momentum projection method for soot prediction in gasification conditions.