Process Design and Optimization of Hybrid ExtractionDistillation Process

Process Design and Optimization of Hybrid Extraction-Distillation Process Systems Design and Control Laboratory, School of Chemical Engineering, Yeungnam University Dae-dong 214 -1, Gyeongsan 712 -749, Rep. of KOREA Phone: +82 53 810 3241, Fax: +82 53 811 3262, Email: mynlee@yu. ac. kr BACKGROUND OF RESEARCH Dehydration of chemicals (such as acetic acid, furfural, 2, 3 butanediol) from aqueous solutions is industrially and environmentally significant. Hybrid of extraction and distillation is considered to be a comparatively effective method because of it is expected has lower energy cost. Design of extractor and determining the optimum stage for obtaining the desired components require the knowledge of LLE data. Binary parameters in activity coefficient models for several components are not available. The experimental data was regressed using the models to obtain the binary parameters. The binary parameter data is essential in the simulation, design, and optimization. . LLE EXPERIMENTAL AND DATA PROCESS DEVELOPMENT REGRESSION Extract: AA Rich Phase Feed: Water, AA, PX Raffinate: Water Rich Phase Solvent: MA or EA Aspen Plus was used for mathematical modelling to build up the regression parameter. This software was used due to flexibility for doing simulation in further steps. Fig. 2 showed the flowchart of data regression from LLE experiments to get the predicted data. Calculate Distribution Coefficient and Separation Factor Gas Chromatograph and Karl-Fischer Analysis LLE Quaternary Experiments Check the Reliability of Experimental Data Regression using NRTL and UNIQUAC in Aspen Plus v 8. 4 Binary Parameters Calibration Calculate RMSD Glance Concept of Hybrid Extraction-Distillation APPLICATION Flowchart of Data Regression from Experimental Data to get Predicted Data OPTIMIZATION Aspen Optimization – SQP Sequential Optimization Example of Industrial application of hybrid extractiondistillation