Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152264
Title: Do particle-related parameters influence circulating fluidized bed (CFB) riser flux and elutriation?
Authors: Chew, Jia Wei
Cocco, Ray A.
Keywords: Engineering::Chemical technology
Issue Date: 2020
Source: Chew, J. W. & Cocco, R. A. (2020). Do particle-related parameters influence circulating fluidized bed (CFB) riser flux and elutriation?. Chemical Engineering Science, 227, 115935-. https://dx.doi.org/10.1016/j.ces.2020.115935
Project: 2019-T1-002-065
Journal: Chemical Engineering Science
Abstract: In fluidized bed systems, particle properties (e.g., particle diameter, Reynolds number) are acknowledged to be important in dictating various fluidization phenomena, and are thereby commonly included in empirical correlations and physical models. The goal of this study was to harness machine learning tools to determine the relative dominance of the parameters in riser flux and elutriation to provide insights in advancing such predictive tools. The 1320 dataset involved monodisperse, binary, and polydisperse Geldart Group B particles investigated in a pilot-scale circulating fluidized bed riser. Regarding both riser flux and elutriation, (i) random forest ranking and self-organizing map (SOM) weight planes indicate that the pressure at the riser bottom was by far the most dominant relative to the particle-related parameters; and (ii) the neural network model based on the pressure at the riser bottom alone gave an R² of almost 1, affirming the lack of influence of particle-related properties.
URI: https://hdl.handle.net/10356/152264
ISSN: 0009-2509
DOI: 10.1016/j.ces.2020.115935
Rights: © 2020 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCBE Journal Articles

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