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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
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Phase Equilibria Simulation of Biomaterial-Hydrogen Binary Systems Using a Simple Empirical Correlation
Language: English
Date: 11 April 2023
Place of Publication: Darmstadt
Year of primary publication: 2023
Publisher: MDPI
Journal or Publication Title: Processes
Volume of the journal: 11
Issue Number: 3
Collation: 12 Seiten
DOI: 10.26083/tuprints-00023350
Corresponding Links:
Origin: Secondary publication DeepGreen

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.

Uncontrolled Keywords: biochemical–hydrogen binary system, empirical correlation, artificial neural networks, equations of state, comparative analyses
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-233501
Additional Information:

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

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institut für Energiesysteme und Energietechnik (EST)
Date Deposited: 11 Apr 2023 12:01
Last Modified: 14 Nov 2023 19:05
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23350
PPN: 509029167
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