Optimal model‐based design of experiments for parameter precision: Supercritical extraction case

Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent. The concept of quasi‐one‐dimensional flow is applied to reduce the number of spatial dimensions. The flow is assumed to be uniform across any cross‐section, although the area available for the fluid phase can vary along the extractor. The physical properties of the solvent are estimated from the Peng–Robinson equation of state. The empirical correlations used in the model are based on laboratory experiments performed under multiple constant operating conditions: , bar, and kg/s. A model‐based design of experiments with the D‐optimality criterion is applied to improve the precision of the correlation parameters by designing a new dynamic experiment. The mass flow rate and inlet temperature are used as decision variables to maximize the Fisher information embedded in the yield curve with respect to the empirical correlations.