Mechanistic modeling and CFD simulation of gas chromatography to predict separation processes

Gas chromatography (GC) is a frequently applied separation technique. Nevertheless, a suitable operational setup for reaching separation may require extensive time and resources. Mathematical models have been used to predict chromatographic parameters and to propose the analysis conditions; however, the use of empirical correlations has limited application and may be inaccurate. This work proposed a precise physical-based mathematical model using mechanistic equations to describe GC under constant pressure and constant flow, aiming to predict holdup time and the full separation process in a CFD software. A bidimensional model was validated by the description of the mobile phase flow and compounds elution, allowing to predict the chromatographic parameters in both GC operating modes. The observed errors were less than 5% for all predicted parametric values, which is around the input parameter uncertainty. The 2D approach allowed a relatively quick computational time to describe with high accuracy the evaluated parameters, concentration profile, and an operational setup for separating the compounds.