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Phase Equilibria Simulation of Biomaterial-Hydrogen Binary Systems Using a Simple Empirical Correlation

Faress, Fardad ; Pourahmad, Afham ; Abdollahi, Seyyed Amirreza ; Safari, Mohammad Hossein ; Mozhdeh, Mozhgan ; Alobaid, Falah ; Aghel, Babak (2023)
Phase Equilibria Simulation of Biomaterial-Hydrogen Binary Systems Using a Simple Empirical Correlation.
In: Processes, 2023, 11 (3)
doi: 10.26083/tuprints-00023350
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

This study proposes a simple correlation for approximating hydrogen solubility in biomaterials as a function of pressure and temperature. The pre-exponential term of the proposed model linearly relates to the pressure, whereas the exponential term is merely a function of temperature. The differential evolution (DE) optimization algorithm helps adjust three unknown coefficients of the correlation. The proposed model estimates 134 literature data points for the hydrogen solubility in biomaterials with an excellent absolute average relative deviation (AARD) of 3.02% and a coefficient of determination (R) of 0.99815. Comparing analysis justifies that the developed correlation has higher accuracy than the multilayer perceptron artificial neural network (MLP-ANN) with the same number of adjustable parameters. Comparing analysis justifies that the Arrhenius-type correlation not only needs lower computational effort, it also has higher accuracy than the PR (Peng-Robinson), PC-SAFT (perturbed-chain statistical associating fluid theory), and SRK (Soave-Redlich-Kwong) equations of state. Modeling results show that hydrogen solubility in the studied biomaterials increases with increasing temperature and pressure. Furthermore, furan and furfuryl alcohol show the maximum and minimum hydrogen absorption capacities, respectively. Such a correlation helps in understanding the biochemical–hydrogen phase equilibria which are necessary to design, optimize, and control biofuel production plants.

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Faress, Fardad ; Pourahmad, Afham ; Abdollahi, Seyyed Amirreza ; Safari, Mohammad Hossein ; Mozhdeh, Mozhgan ; Alobaid, Falah ; Aghel, Babak
Art des Eintrags: Zweitveröffentlichung
Titel: Phase Equilibria Simulation of Biomaterial-Hydrogen Binary Systems Using a Simple Empirical Correlation
Sprache: Englisch
Publikationsjahr: 2023
Ort: Darmstadt
Publikationsdatum der Erstveröffentlichung: 2023
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Processes
Jahrgang/Volume einer Zeitschrift: 11
(Heft-)Nummer: 3
Kollation: 12 Seiten
DOI: 10.26083/tuprints-00023350
URL / URN: https://tuprints.ulb.tu-darmstadt.de/23350
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Herkunft: Zweitveröffentlichung DeepGreen
Kurzbeschreibung (Abstract):

This study proposes a simple correlation for approximating hydrogen solubility in biomaterials as a function of pressure and temperature. The pre-exponential term of the proposed model linearly relates to the pressure, whereas the exponential term is merely a function of temperature. The differential evolution (DE) optimization algorithm helps adjust three unknown coefficients of the correlation. The proposed model estimates 134 literature data points for the hydrogen solubility in biomaterials with an excellent absolute average relative deviation (AARD) of 3.02% and a coefficient of determination (R) of 0.99815. Comparing analysis justifies that the developed correlation has higher accuracy than the multilayer perceptron artificial neural network (MLP-ANN) with the same number of adjustable parameters. Comparing analysis justifies that the Arrhenius-type correlation not only needs lower computational effort, it also has higher accuracy than the PR (Peng-Robinson), PC-SAFT (perturbed-chain statistical associating fluid theory), and SRK (Soave-Redlich-Kwong) equations of state. Modeling results show that hydrogen solubility in the studied biomaterials increases with increasing temperature and pressure. Furthermore, furan and furfuryl alcohol show the maximum and minimum hydrogen absorption capacities, respectively. Such a correlation helps in understanding the biochemical–hydrogen phase equilibria which are necessary to design, optimize, and control biofuel production plants.

Freie Schlagworte: biochemical–hydrogen binary system, empirical correlation, artificial neural networks, equations of state, comparative analyses
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-233501
Zusätzliche Informationen:

This article belongs to the Special Issue Advanced Technology of Biomass Gasification Processes

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Energiesysteme und Energietechnik (EST)
Hinterlegungsdatum: 11 Apr 2023 12:01
Letzte Änderung: 12 Apr 2023 04:59
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