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http://hdl.handle.net/2080/856
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| Title: | Artificial Neural Network Approach to Segregation Characteristic of Binary Heterogeneous Mixtures in Promoted Gas-Solid Fluidized Beds |
| Authors: | Sahoo, A
Roy, G K |
| Keywords: | Artificial neural network approach
Coaxial promoters
Gas-solid fluidization
Heterogeneous binary mixtures
Segregation distance |
| Issue Date: | 2008 |
| Publisher: | Taylor & Francis |
| Citation: | Taylor & Francis, Particulate Science and Technology, Volume 26, Issue 6, November 2008, Pages 574-586 |
| Abstract: | Binary mixtures of particles of the same size but of different densities are fluidized in a 15 cm diameter column with a perforated plate distributor and two coaxial promoters. In the present work an attempt has been made to study the fluidization and the segregation characteristic of density-variant solids of the same size in terms of segregation distance. The dimensionless segregation distance has been correlated with other dimensionless groups relating to various system parameters: ratio of the density of jetsam particles to that of flotsam, initial static bed height, height of layer of particles above the bottom grid, superficial gas velocity, and average density of the mixture on the basis of the dimensional analysis approach for both un-promoted and promoted beds. Correlations have also been developed with the above system parameters by using an artificial neural network approach for different types of fluidized beds, and the findings with respect to both approaches have been com... |
| URI: | http://dx.doi.org/10.1080/02726350802498756
http://hdl.handle.net/2080/856 |
| Appears in Collections: | Journal Articles
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