Liquid-Liquid Equilibrium Data Correlation: Predicting A Robust and Consistent Set of Initial NRTL Parameters (GUI: ParamIni_LL_NRTL)

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Título: Liquid-Liquid Equilibrium Data Correlation: Predicting A Robust and Consistent Set of Initial NRTL Parameters (GUI: ParamIni_LL_NRTL)
Título alternativo: Graphical User Interface (GUI): ParamIni_LL_NRTL
Autor/es: Labarta, Juan A. | Caballero, José A. | Marcilla, Antonio
Grupo/s de investigación o GITE: Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT) | Procesado y Pirólisis de Polímeros
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Ingeniería Química
Palabras clave: NRTL model | LLE | Fluid phase equilibria | Correlation data | Consistency | Binary interection parameters | ESCAPE33 | ParamIni_LL_NRTL | GUI | Graphical user interface
Fecha de creación: 13-nov-2022
Fecha de publicación: 30-mar-2023
Resumen: 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.
Descripción: 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).
Patrocinador/es: 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
Idioma: eng
Tipo: info:eu-repo/semantics/conferenceObject
Derechos: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)
Revisión científica: si
Aparece en las colecciones:INV - GTP3 - Comunicaciones a Congresos
INV - CONCEPT - Comunicaciones a Congresos, Conferencias, etc.

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