Please use this identifier to cite or link to this item:
Title: Self-optimization of distillation sequences using DSE parameter
Other Titles: Auto-optimització de trens de columnes de destil·lació mitjançant la eficiència de la seqüència de destil·lació (DSE)
Author: Parra Paz, Alex
Director/Tutor: Bonet i Ruiz, Jordi
Bonet Ruiz, Alexandra
Keywords: Destil·lació
Treballs de fi de grau
Bachelor's thesis
Issue Date: Jun-2016
Abstract: To perform an azeotropic ternary mixture separation, several distillation sequence are feasible to separate the three compounds of the mixture. Due to the great complexity of the process the mathematical model is simplified according to the ∞/∞ analysis assumptions, i.e. columns of infinite length operated at the infinite reflux. The objective function is the overall process energy requirements that in previous studies was approximated to the overall process distillate flow rate. The problem of this optimization function is that it does not take into account the facility or difficulty to perform this separation and the efficiency of the columns. The originality of the present study is that the distillation sequence efficiency (DSE) of the overall process is used as the optimization function. The energy requirement depends on the crude feed composition. The novel method is applied to a case study for the separation of a crude feed formed by methanol, 2-propanol and water. The aim of this project is to compare the results previously obtained by Ulrich and Morari (2003) minimizing the overall distillate flow rate with the results maximizing the DSE, i.e. the efficiency of the columns is taken into account.
Note: Treballs Finals de Grau d'Enginyeria Química, Facultat de Química, Universitat de Barcelona, Curs: 2015-2016, Tutors: Jordi Bonet i Ruiz i Alexandra Elena Bonet Ruiz
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Química

Files in This Item:
File Description SizeFormat 
PARRA PAZ, ALEX 2015-16 P.pdf1.47 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons