文献类型：期刊文献

英文题名：Numerical simulation of a slagging fixed bed refuse-derived fuel gasifier by using two-fluid model

作者：Zeng, Wei[1];Yan, Shuai[2];Xia, Zihong[1]

机构：[1]East China Univ Sci & Technol, Dept Energy & Chem Engn, Shanghai 200237, Peoples R China;[2]Ningbo Univ Technol, Sch Mat & Chem Engn, Ningbo 315211, Peoples R China

年份：2026

卷号：417

外文期刊名：FUEL

收录：;EI(收录号：20260620031483);WOS:【SCI-EXPANDED(收录号:WOS:001684838500001)】；

基金：This work was supported by the project of the National Key Research and Development Program of China (2024YFB4006701) and Yongjiang Talent Program (2024A-137-G) .

语种：英文

外文关键词：Slagging fixed bed gasifier; Two-fluid model; Oxygen-to-fuel ratio; Steam-to-oxygen ratio

摘要：A novel two-fluid model was developed for slagging fixed bed refuse-derived fuel (RDF) gasifiers by adopting a zonal modelling approach to characterize distinct flow behaviors in different regions. According to different treatments of the solid phase, the gasifier is divided into three zones, namely the falling zone, the moving zone and the raceway zone. The model was validated against experimental data from a benchmark case, demonstrating its ability to accurately capture the staged thermochemical conversion processes and predict outlet gas composition. Analysis reveals a clear temperature gradient along the bed height, enabling identification of four distinct reaction zones: drying, devolatilization, gasification and combustion. The validated model was further employed to optimize operating conditions, such as the oxygen-to-fuel and steam-to-oxygen ratios. Results show that an oxygen-to-fuel ratio of 0.08 provides balanced performance, whereas excessively low ratios cause temperature drops and reduce gasification efficiency, and overly high ratios promote excessive combustion of hydrogen. In addition, moderately increasing the steam-to-oxygen ratio can enhance syngas yield but is constrained by the associated water-gas shift reaction. These findings offer valuable insights for the design and regulation of slagging fixed bed gasifiers, demonstrating the model's effectiveness in predicting performance and guiding operational optimization.