High-definition simulation of packed-bed liquid chromatography

Jayghosh Subodh Rao, Andreas Püttmann, Siarhei Khirevich, Ulrich Tallarek, Christophe Geuzaine, Marek Behr, Eric von Lieres

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Numerical simulations of chromatography are conventionally performed using reduced-order models that homogenize aspects of flow and transport in the radial and angular dimensions. This enables much faster simulations at the expense of lumping the effects of inhomogeneities into a column dispersion coefficient, which requires calibration via empirical correlations or experimental results. We present a high-definition model with spatially resolved geometry. A stabilized space–time finite element method is used to solve the model on massively parallel high-performance computers. We simulate packings with up to 10,000 particles. The impact of particle size distribution on velocity and concentration profiles as well as breakthrough curves is studied. Our high-definition simulations provide unique insight into the process. The high-definition data can also be used as a source of ground truth to identify and calibrate appropriate reduced-order models that can then be applied for process design and optimization.
Original languageEnglish (US)
Pages (from-to)108355
JournalComputers and Chemical Engineering
Volume178
DOIs
StatePublished - Jul 31 2023

ASJC Scopus subject areas

  • General Chemical Engineering
  • Computer Science Applications

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