1. Process Design and Optimization of Hybrid Extraction-Distillation
                          
                                                            
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 , Rep. of KOREA Phone: , Fax: ,
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 REGRESSION
PROCESS DEVELOPMENT
Feed: Water, AA, PX
Solvent: MA or EA
Extract: AA Rich Phase
Raffinate: Water Rich Phase
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.
LLE Quaternary Experiments
Gas Chromatograph and Karl-Fischer Analysis
Regression using NRTL and UNIQUAC in Aspen Plus v8.4
Binary Parameters
Calibration
Calculate RMSD
Calculate Distribution Coefficient and Separation Factor
Check the Reliability of Experimental Data
Glance Concept of Hybrid Extraction-Distillation
APPLICATION
Flowchart of Data Regression from Experimental Data to get Predicted Data
OPTIMIZATION
Sequential Optimization
Aspen Optimization – SQP
Example of Industrial application of hybrid extraction-distillation