prikaz prve stranice dokumenta Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network
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Scientific paper - Original scientific paper
Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network
Cleaner Engineering and Technology, 1 (2020); 100029. https://doi.org/10.1016/j.clet.2020.100029
Cerinski, Damijan; Baleta, Jakov; Mikulčić, Hrvoje; Mikulandrić, Robert; Wang, Jin

Institutional repository: Repository of Faculty of Metallurgy University of Zagreb

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Cerinski, D., Baleta, J., Mikulčić, H., Mikulandrić, R. & Wang, J. (2020). Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network. Cleaner Engineering and Technology, 1.. doi: 10.1016/j.clet.2020.100029

Cerinski, Damijan, et al. "Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network." Cleaner Engineering and Technology, vol. 1, 2020. https://doi.org/10.1016/j.clet.2020.100029

Cerinski, Damijan, Jakov Baleta, Hrvoje Mikulčić, Robert Mikulandrić and Jin Wang. "Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network." Cleaner Engineering and Technology 1 (2020). https://doi.org/10.1016/j.clet.2020.100029

Cerinski, D., et al. (2020) 'Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network', Cleaner Engineering and Technology, 1. doi: 10.1016/j.clet.2020.100029

Cerinski D, Baleta J, Mikulčić H, Mikulandrić R, Wang J. Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network. Cleaner Engineering and Technology [Internet]. 2020 December [cited 2024 November 30];1. doi: 10.1016/j.clet.2020.100029

D. Cerinski, J. Baleta, H. Mikulčić, R. Mikulandrić and J. Wang, "Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network", Cleaner Engineering and Technology, vol. 1, December 2020. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:115:893992. [Accessed: 30 November 2024]

Metadata
Title (english)Dynamic modelling of the biomass gasification process in a fixed bed reactor by using the artificial neural network
AuthorDamijan Cerinski
AuthorJakov Baleta
AuthorHrvoje Mikulčić
AuthorRobert Mikulandrić
AuthorJin Wang
Author's institutionUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
(Department of Energy, Power and Environmental Engineering)
(Power Engineering and Energy Management Chair)
Author's institutionUniversity of Zagreb
Faculty of Metallurgy
(Department of Mechanical Metallurgy)
(Laboratory of Thermal Technics and Mechanical Engineering)
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Abstract (english)
Biomass gasification enables the transformation of biomass feedstock into syngas suitable for further energy conversions. Mathematical models of gasification are not only valuable tool for the design and optimization of the processes, but could be also employed for online prediction and process control. In this work, the potential of using nonlinear autoregressive networks with exogenous inputs (NARX) for predicting the gasification process when a lower amount of experimental data is available was studied. The analysis of using an open-loop NARX network for an online prediction of the syngas composition in a downdraft gasifier at different data recording frequency was performed. The predicted results showed that by decreasing the data recording frequency, the prediction error increases. Furthermore, the possibility of improving the NARX network at lower data recording frequency was analysed by expanding the training dataset to reduce discrepancies between predicted and measured results. Inclusion of four data sets made neural network more robust and flexible for operating with fewer data points. Practical significance of results can be seen in the application of open-loop network for online prediction and control of the gasification process at lower data recording frequency as a part of a model predictive control module.
Keywords (croatian)
Languagecroatian
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleCleaner Engineering and Technology
Numberingvol. 1, 100029
p-ISSN2666-7908
DOIhttps://doi.org/10.1016/j.clet.2020.100029
URN:NBNurn:nbn:hr:115:893992
Publication2020-12
Document URLhttps://linkinghub.elsevier.com/retrieve/pii/S266679082030029X
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) icon
Created on2024-05-03 16:38:58