Modeling of product temperature in a supercritical fluid extrusion process through dimensional analysis

Abstract

AbstractA correlation model for predicting the maximum product temperature reached during a supercritical fluid extrusion (SCFX) process was developed using the Buckingham Pi method. Two dimensionless groups, Dref (ratio of screw diameter to screw length) and Eref (ratio of energy added to energy removed), were developed to model the maximum temperature of an SCFX process using dimensional analysis. The model was validated by comparing predicted and experimental values. Experiments were conducted using two feed formulations: 1. Milk protein concentrate (MPC) with rice flour (30%), and 2. MPC with grape pomace (15%). The average percent error was 2.57% for rice flour extrudate and 1.02% for grape pomace extrudate. Based on the results, the model could be used for prediction of maximum temperature in SCFX systems.Practical ApplicationsMaintaining the extruder temperature below 100°C remains a major challenge during the supercritical fluid extrusion (SCFX) process. The model developed determines the maximum temperature of a given SCFX system based on key extrusion parameters. Hence, the developed model can be used by manufacturers for determining the optimal operating conditions while scaling up an SCFX process.