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Benchmark Database Containing Binary-System-High-Quality- Certified Data for Cross-Comparing Thermodynamic Models and Assessing Their Accuracy

Abstract : In the last two centuries, equations of state (EoSs) have become a key tool for the correlation and prediction of thermodynamic properties of fluids. They not only can be applied to pure substances as well as to mixtures but also constitute the heart of commercially available computer-aided-process-design software. In the last 20 years, thousands of publications have been devoted to the development of sophisticated models or to the improvement of already existing EoSs. Chemical engineering thermodynamics is thus a field under steady development, and to assess the accuracy of a thermodynamic model or to cross-compare two models, it is necessary to confront model predictions with experimental data. In this context, the importance of a reliable free-to-access benchmark database is pivotal and becomes absolutely necessary. The goal of this paper is thus to present a database, specifically designed to assess the accuracy of a thermodynamic model or cross-compare models, to explain how it was developed and to enlighten how to use it. A total of 200 nonelectrolytic binary systems have been selected and divided into nine groups according to the associating character of the components, i.e., their ability to be involved in a hydrogen bond (the nature and strength of the association phenomena are indeed considered a measure of the complexity to model the thermodynamic properties of mixtures). The methodology for assessing the performance of a given model is then described. As an illustration, the Peng− Robinson EoS with classical van der Waals mixing rules and a temperature-dependent binary interaction parameter (k ij) have been used to correlate the numerous data included in the proposed database, and its performance has been assessed following the proposed methodology.
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https://hal.univ-lorraine.fr/hal-02921996
Contributor : Jean-Noël Jaubert <>
Submitted on : Tuesday, August 25, 2020 - 4:43:04 PM
Last modification on : Monday, March 29, 2021 - 4:07:31 PM
Long-term archiving on: : Tuesday, December 1, 2020 - 7:27:34 AM

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Jean-Noel Jaubert, Yohann Le Guennec, Andreś Pinã-Martinez, Nicolas Ramirez-Velez, Silvia Lasala, et al.. Benchmark Database Containing Binary-System-High-Quality- Certified Data for Cross-Comparing Thermodynamic Models and Assessing Their Accuracy. Industrial and engineering chemistry research, American Chemical Society, 2020, 59 (33), pp.14981-15027. ⟨10.1021/acs.iecr.0c01734⟩. ⟨hal-02921996⟩

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