Liquid-Liquid Equilibrium Data Correlation: Predicting A Robust and Consistent Set of Initial NRTL Parameters (GUI: ParamIni_LL_NRTL)
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10045/134753
Title: | Liquid-Liquid Equilibrium Data Correlation: Predicting A Robust and Consistent Set of Initial NRTL Parameters (GUI: ParamIni_LL_NRTL) |
---|---|
Other Titles: | Graphical User Interface (GUI): ParamIni_LL_NRTL |
Authors: | Labarta, Juan A. | Caballero, José A. | Marcilla, Antonio |
Research Group/s: | Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT) | Procesado y Pirólisis de Polímeros |
Center, Department or Service: | Universidad de Alicante. Departamento de Ingeniería Química |
Keywords: | NRTL model | LLE | Fluid phase equilibria | Correlation data | Consistency | Binary interection parameters | ESCAPE33 | ParamIni_LL_NRTL | GUI | Graphical user interface |
Date Created: | 13-Nov-2022 |
Issue Date: | 30-Mar-2023 |
Abstract: | In the present work, the NRTL model has been analyzed to obtain a good representation of the different ternary liquid-liquid equilibria that this thermodynamic model can reproduce satisfactorily. To do that, the main characteristics of different possible binary subsystems, ternary binodal curves (location in the composition diagram, size, tie-lines orientation, and plait point location), and LLLE tie triangles have been evaluated. With more than two hundred systems studied, the different behaviors have been parametrized to create, as the main objective of the present work, a database and a graphical user interface associated (ParamIni_LL_NRTL, Labarta et al. 2022. RUA: http://hdl.handle.net/10045/130017). This resource (publicly available for teaching and research uses) allows, given a set of ternary experimental LLE data to obtain by comparison with the elements of the database, a consistent set of initial NRTL parameters (taui,j, alfai,j) to start the corresponding correlation data procedure with enough guarantees. |
Description: | 33rd European Symposium on Computer Aided Process Engineering (ESCAPE33), June 18-21, 2023, Athens, Greece (Theme 8. Education and knowledge transfer: Poster 43,Board 107). |
Sponsor: | The authors gratefully acknowledge the financial support by the Ministry of Science and Innovation from Spain, under the project PID2021-124139NB-C21: SUS4Energy, 2022/00666/001 (AEI). |
URI: | http://hdl.handle.net/10045/134753 |
Language: | eng |
Type: | info:eu-repo/semantics/conferenceObject |
Rights: | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0) |
Peer Review: | si |
Appears in Collections: | INV - GTP3 - Comunicaciones a Congresos INV - CONCEPT - Comunicaciones a Congresos, Conferencias, etc. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ReferencesList_GUI_ParamIni_LL_NRTL.pdf | Full list of poster references | 125,36 kB | Adobe PDF | Open Preview |
Poster43_107_GUI_ParamIni_LL_NRTL.pdf | Main poster | 439,72 kB | Adobe PDF | Open Preview |
This item is licensed under a Creative Commons License