The mesoscale packing structure and its coupling with the gas flow and heterogeneous reaction kinetics are key for CO₂ capture using CaO-based sorbents. A series of packing structures were constructed based on the discrete-element method (DEM), and the accuracy was verified by electronic computer X-ray tomography (CT). It was found that the random particle filling structure based on the DEM can accurately reflect the coordination number and connectivity between pores. Further, a two-dimensional pore network model (PNM) including the effects of packing structure evolution and diffusion–reaction kinetics was developed to study the multiscale coupling among gas flow, energy transport, and carbonation reactions in packed-bed reactors. The calculated results were validated by comparison with experimental data from thermogravimetric analyzer (TGA) tests during the CO₂ capture process. The short-circuit flow of the reactive gas caused by the inhomogeneous packing structure of the binary composite packing bed was not linearly correlated with the mass percentage of the binary particles. The differences in the CO₂ capture efficiency and sorbent utilization induced by the packing structure characteristics were demonstrated numerically to decrease gradually with the Peclet number at an inlet velocity of 0.8 m/s. Moreover, a dimensionless Thiele modulus was introduced to assess the effect of internal diffusion. This model and the obtained results can be used for the optimization and design of packed-bed reactors with gas–solid uncatalyzed reactions.

中文翻译：

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CO2 捕集期间的跨尺度传递和反应耦合：基于 DEM-PNM 的新型孔隙到反应器尺度模型

介观尺度堆积结构及其与气流和非均相反应动力学的耦合是使用CaO基吸附剂捕获CO ₂的关键。基于离散元法（DEM）构建了一系列封装结构，并通过电子计算机X射线断层扫描（CT）验证了其精度。结果发现，基于DEM的随机颗粒填充结构能够准确反映孔隙之间的配位数和连通性。此外，还开发了包含填充结构演化和扩散反应动力学影响的二维孔隙网络模型（PNM），用于研究填充床反应器中气流、能量传输和碳酸化反应之间的多尺度耦合。通过与CO ₂捕获过程中热重分析仪（TGA）测试的实验数据进行比较，验证了计算结果。二元复合填料床的不均匀堆积结构引起的反应气体的短路流量与二元颗粒的质量百分比不呈线性相关。数值模拟表明，在入口速度为0.8 m/s 时，填料结构特征引起的CO ₂捕集效率和吸附剂利用率的差异随着佩克莱特数逐渐减小。此外，引入无量纲蒂勒模量来评估内部扩散的影响。该模型和所得结果可用于气固非催化反应填充床反应器的优化和设计。