| Title: | Anaerobic digestion BioModel upgraded by various inhibition types |
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| Authors: | ID Kegl, Tina (Author) |
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| Files: |  1-s2.0-S0960148124004920-main.pdf (14,85 MB)
MD5: 83677A9006EE0736B0BCB74C3985DD3A
 https://www.sciencedirect.com/science/article/pii/S0960148124004920?via%3Dihub
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FKKT - Faculty of Chemistry and Chemical Engineering
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| Abstract: | This work deals with numerical simulation of the anaerobic digestion process. Special attention is focused on the inhibitions modeling. For this purpose, an existing complex BioModel is upgraded by adequate modeling of non-competitive, competitive, and uncompetitive inhibition types. The obtained results of sensitivity analysis shows that various inhibition constants are ranged within the most important model parameters. For each inhibition type, the upgraded model is calibrated and validated with respect to the measured anaerobic digestion performance in CSTR bioreactors of a full scale biogas plant in period of two years. The obtained statistical indicators differ up to 5% in model calibration and validation. The best values of relative index of agreement for CH4 and H2S flow rates were obtained when using competitive inhibition; their values were 0.9385 and 0.7903, respectively. For H2 flow rate and pH value, the best indices of 0.7945 and 0.6593 were obtained with uncompetitive inhibition. For biogas flow rate, the best index of 0.9518 was obtained when using non-competitive inhibition. Since no inhibition type delivers best results in all situations, further research is needed to model mixed inhibition type for various inhibitors. |
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| Keywords: | BioModel, inhibition modeling, model parameters calibration, active set optimization procedure, gadient-based optimization |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 10.09.2023 |
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| Article acceptance date: | 30.03.2024 |
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| Publication date: | 31.03.2024 |
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| Publisher: | Elsevier |
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| Year of publishing: | 2024 |
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| Number of pages: | 16 str. |
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| Numbering: | Vol. 226, [article no.] 120427 |
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| PID: | 20.500.12556/DKUM-90153  |
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| UDC: | 66.02 |
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| ISSN on article: | 1879-0682 |
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| COBISS.SI-ID: | 191356163 |
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| DOI: | 10.1016/j.renene.2024.120427 |
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| Copyright: | © 2024 The Author |
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| Publication date in DKUM: | 23.08.2024 |
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| Views: | 244 |
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| Downloads: | 25 |
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| Metadata: |    |
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| Categories: | Misc.
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