Nik Norizam, N.N.A. orcid.org/0000-0001-8793-2940, Yang, X., Azri, N. et al. (4 more authors) (2025) An improved numerical model for early detection of bed agglomeration in fluidized bed combustion. Journal of the Energy Institute, 119. 101987. ISSN 1743-9671
Abstract
An improved predictive numerical index has been developed to predict the tendency of bed agglomeration in fluidized bed boilers. The index was developed based on the melt fraction resulting from the thermodynamic equilibrium model of fuel ash compositions together with SiO2 as the bed material at temperatures ranging from 700 to 900 °C. The partial least squares regression (PLSR) coupled with the cross-validation technique is utilized to establish the correlation for the bed agglomeration index, Ia. The improved index, Ia has been validated by experimental observations found in various literature sources. The results obtained using the improved index, Ia demonstrated a significantly higher success rate in predicting the bed agglomeration tendency of biomass fuel ash compared to the other four conventional bed agglomeration indices. In addition, K2O is the main element that accelerates the formation of bed agglomeration in the biomass firing while CaO was found to reduce the tendency of bed agglomeration in the fluidized bed combustion system.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Journal of the Energy Institute is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Chemical Engineering; Engineering |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jan 2025 09:53 |
Last Modified: | 17 Jan 2025 14:51 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.joei.2025.101987 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:221937 |