|
DSpace@nitr >
National Institue of Technology- Rourkela >
Journal Articles >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/347
|
| Title: | Artificial Neural Network Approach to Segregation Characteristic of Binary Homogeneous Mixtures in Promoted Gas Solid Fluidized Beds |
| Authors: | Sahoo, A
Roy, G K |
| Keywords: | Binary mixtures
Segregation distance
Co-axial promoters
Gas-solid fluidization
Artificial Neural Network |
| Issue Date: | 2006 |
| Publisher: | Elsevier |
| Citation: | Powder Technology, (Accepted post-print) |
| Abstract: | Binary mixtures of size-different dolomites are fluidized in a bed where co-axial promoters are introduced. The segregation characteristic of jetsam particles has been determined for different mixtures in terms of the segregation distance by empirically correlating the results with the various system parameters viz. initial static bed height, height of a layer of particles above the bottom grid, superficial gas velocity and average particle size of the mixture with dimensional analysis for both the un-promoted and the promoted beds. Correlations have also been developed with the above system parameters from an Artificial Neural Network approach. Segregation distances for the promoted and un-promoted beds have been compared. The results through the correlations thus developed with the above system parameters from ANN approach and the findings with respect to the dimensional analysis approach have been compared. |
| Description: | Copyright for the published version belongs to Elsevier. This is Author's post print Version |
| URI: | http://hdl.handle.net/2080/347 |
| Appears in Collections: | Journal Articles
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| Asahoo-2006-pow.pdf | | 316Kb | Adobe PDF | View/Open |
|
Show full item record
All items in DSpace are protected by copyright, with all rights reserved.
|
