Increasing the Informativeness of Supercritical Fluid Extraction Experiments

Abstract

Abstract: The bayesian approach and Markov chain Monte Carlo method are used to evaluate the effective process parameters (diffusion coefficient, oil saturation concentration in the solvent, initial oil content in the raw material) of supercritical fluid extraction (SFE) of oil from ground apricot kernels. It is shown that these parameters can be inferred more accurately within the shrinking core model if the experimental data include the results of at least two experiments—with finely and coarsely ground raw material.