Particle transport method for simulation of multicomponent chromatography problems

Area of Science:

• Chemical Engineering
• Computational Chemistry
• Numerical Analysis

Background:

• Multicomponent chromatography with non-linear isotherms presents significant simulation challenges.
• Accurate modeling is crucial for optimizing separation processes and understanding complex chemical interactions.

Purpose of the Study:

• To introduce and evaluate a novel numerical technique, the particle transport method (PTM), for simulating multicomponent chromatography.
• To assess the accuracy, computational efficiency, and mass conservation of PTM compared to existing methods.

Main Methods:

• The particle transport method (PTM) utilizes an operator-splitting approach, combining the Lagrangian method of characteristics and the method of lines.
• PTM employs a set of interpolable numerical particles instead of a moving mesh, incorporating spatial adaptivity for steep front simulation.
• The method was applied to two-component systems with competitive Langmuir and Fowler isotherms, simulating both ideal and non-ideal chromatographic models.

Main Results:

• PTM demonstrated good mass conservation across various simulation scenarios.
• The numerical experiments showed PTM to be a computationally inexpensive scheme.
• Comparisons with classical methods like OCFEM, MOL, and the Rouchon algorithm indicated favorable accuracy and speed for PTM.

Conclusions:

• The particle transport method (PTM) is an effective and efficient numerical technique for simulating multicomponent chromatography with non-linear isotherms.
• PTM's spatial adaptivity and particle-based approach are well-suited for handling steep fronts (shock waves) common in non-linear chromatography.
• PTM offers a promising alternative to existing methods, balancing accuracy, computational cost, and mass conservation.