We present four different numerical methods for the numerical simulation of simulated moving bed chromatography. Two approaches use fixed-point iteration for computing cyclic steady states, and two other approaches use operator splitting for computing complete system trajectories. All methods are based on weak coupling of individual column models and can easily be implemented using any existing single-column solver. Simulation software is implemented based on the CADET project and published as open source code.

The numerical performance is compared using five case studies. For both fixed-point iteration and operator-splitting, an alternative approach is found to be more efficient than the standard approach. Namely, the one-column analog saves time in computing the cyclic steady state, while lag-aware operator-splitting yields more detailed information on the system trajectory. The presented methods can be combined with other models, for example to consider hold-up volumes, and have applications beyond simulated bed chromatography.

我们提出了四种不同的数值方法，用于模拟移动床色谱的数值模拟。两种方法使用定点迭代来计算循环稳态，而其他两种方法使用算子拆分来计算完整的系统轨迹。所有方法都基于单个色谱柱模型的弱耦合，并且可以使用任何现有的单列求解器轻松实现。仿真软件基于CADET项目实现，并作为开源代码发布。

使用五个案例研究对数值性能进行了比较。对于定点迭代和运算符拆分，发现一种替代方法比标准方法更有效。即，单列模拟节省了计算循环稳态的时间，而滞后感知的运算符分解可提供有关系统轨迹的更详细的信息。提出的方法可以与其他模型结合使用，例如考虑滞留体积，并具有超出模拟床色谱法的应用。