甲醇制烯烃流化床内流化特性的多尺度CFD模拟

近些年,我国成功开发了以煤为原料的甲醇制烯烃(Methanol to Olefins, MTO)生产工艺和技术,带动煤制烯烃产业的快速发展,保障了国家能源安全。流化床式反应器是MTO工业生产的核心反应装置,通过计算流体力学(Computational Fluid Dynamics, CFD)方法深入认知MTO流化床内的流化特性规律具有重要的意义,它可以从理论上更加准确地指导MTO流化床的优化与放大。本工作采用基于宏观?亚网格层次的气泡EMMS曳力和传统TFM耦合计算的多尺度CFD方法,对工业尺度MTO流化床内的多相流化行为进行了三维数值模拟。模拟结果表明,该多尺度CFD方法考虑了气泡结构对气?固相间曳力的影响,能较准确地预测MTO流化床内轴向颗粒浓度的“S-型”分布规律,且得到实验数据的验证;所预测的径向颗粒浓度分布呈现出经典的“环?核”分布规律,气体/颗粒的轴向时均速度在径向上的分布也与实际情况相互佐证,表明该多尺度CFD方法显著改善了基于均匀曳力的传统TFM对于宏观流场的预测能力。下一步工作将多尺度CFD方法拓展应用于MTO流化床优化放大及反应特性的研究。

Multi-scale CFD simulation of fluidization characteristics in a methanol-to-olefin fluidized bed

In recent years, China has successfully developed coal-based methanol to olefins (MTO) production processes and technologies, which has promoted the rapid development of the coal-to-olefins industry and guaranteed national energy security. The fluidized bed reactor is the core reaction device for the industrial production of methanol to olefins. It is of great significance to deeply understand the fluidization characteristics of the MTO fluidized bed through computational fluid dynamics. It can give more accurate guide for optimization and amplification of MTO fluidized bed. In this work, the multi-scale computational fluid dynamics (CFD) method which is coupling of bubble-based EMMS drag and traditional TFM is adopted to perform 3D simulation of the multi-phase flow behavior inside an industrial-scale MTO fluidized bed. This multi-scale CFD method involves in the influence of the bubble-based structure on the gas-solid drag coefficient. Thus, it can more accurately predict the "S-shaped" distribution of the axial particle concentration inside the MTO fluidized bed, which is consistent with experimental data. The predicted radical distribution of particle concentration presents the classic "core-annulus" flow structure. The predicted distribution of the averaged gas/particle axial-velocity in the radial direction is also mutually confirmed with the actual situation. This multi-scale CFD method significantly improves the predictive ability of the traditional TFM based on uniform drag for the macroscopic flow field. In future, the focus will be put on extending this multi-scale CFD method to the optimization design and reaction characteristics of MTO fluidized bed.