LAPSE:2023.24684
Published Article
LAPSE:2023.24684
Thermodynamics and Machine Learning Based Approaches for Vapor−Liquid−Liquid Phase Equilibria in n-Octane/Water, as a Naphtha−Water Surrogate in Water Blends
Sandra Lopez-Zamora, Jeonghoon Kong, Salvador Escobedo, Hugo de Lasa
March 28, 2023
The prediction of phase equilibria for hydrocarbon/water blends in separators, is a subject of considerable importance for chemical processes. Despite its relevance, there are still pending questions. Among them, is the prediction of the correct number of phases. While a stability analysis using the Gibbs Free Energy of mixing and the NRTL model, provide a good understanding with calculation issues, when using HYSYS V9 and Aspen Plus V9 software, this shows that significant phase equilibrium uncertainties still exist. To clarify these matters, n-octane and water blends, are good surrogates of naphtha/water mixtures. Runs were developed in a CREC vapor−liquid (VL_Cell operated with octane−water mixtures under dynamic conditions and used to establish the two-phase (liquid−vapor) and three phase (liquid−liquid−vapor) domains. Results obtained demonstrate that the two phase region (full solubility in the liquid phase) of n-octane in water at 100 °C is in the 10−4 mol fraction range, and it is larger than the 10−5 mol fraction predicted by Aspen Plus and the 10−7 mol fraction reported in the technical literature. Furthermore, and to provide an effective and accurate method for predicting the number of phases, a machine learning (ML) technique was implemented and successfully demonstrated, in the present study.
Keywords
Machine Learning, n-octane, number of phases, phase stability, vapor–liquid–liquid equilibrium, Water
Suggested Citation
Lopez-Zamora S, Kong J, Escobedo S, Lasa HD. Thermodynamics and Machine Learning Based Approaches for Vapor−Liquid−Liquid Phase Equilibria in n-Octane/Water, as a Naphtha−Water Surrogate in Water Blends. (2023). LAPSE:2023.24684
Author Affiliations
Lopez-Zamora S: Department of Chemical and Biochemical Engineering, Chemical Reactor Engineering Centre, The University of Western Ontario, London, ON N6A 3K7, Canada [ORCID]
Kong J: Department of Chemical and Biochemical Engineering, Chemical Reactor Engineering Centre, The University of Western Ontario, London, ON N6A 3K7, Canada
Escobedo S: Department of Chemical and Biochemical Engineering, Chemical Reactor Engineering Centre, The University of Western Ontario, London, ON N6A 3K7, Canada [ORCID]
Lasa HD: Department of Chemical and Biochemical Engineering, Chemical Reactor Engineering Centre, The University of Western Ontario, London, ON N6A 3K7, Canada
Journal Name
Processes
Volume
9
Issue
3
First Page
413
Year
2021
Publication Date
2021-02-25
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9030413, Publication Type: Journal Article
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LAPSE:2023.24684
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doi:10.3390/pr9030413
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Mar 28, 2023
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