Segregation characteristics of irregular binaries in gas solid fluidized beds——An ANN-approach

• 作 者: Abanti Sahoo Gopendra Kishore Roy
• 机 构: Department of Chemical Engineering National Institute of Technology,Rourkela,769008 Orissa,India,Dep
• 出 处: Particuology
• 发表日期: 2008年03期
• 关键词: Gas-solid fluidization Segregation distance Static bed condition Fluidized bed c

Binary mixtures of irregular materials of different particle sizes and/or particle densities are fluidized in a 15-cm diameter column with a perforated plate distributor.An attempt has been made in this work to determine the segregation characteristics of jetsam particles for both the homogeneous and heterogeneous binary mixtures in terms of segregation distance by correlating it to 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 and/or particle densities of the mixture through the dimensional analysis.Correlation on the basis of Artificial Neural Network approach has also been developed with the above system parameters thereby authenticating the development of correlation by the former approach.The calculated values of the segregation distance obtained for both the homogeneous and heterogeneous binary mixtures from both the types of fluidized beds(i.e.under the static bed condition and the fluidized bed condition) have also been compared with each other.

Binary mixtures of irregular materials of different particle sizes and / or particle densities are fluidized in a 15-cm diameter column with a perforated plate distributor. An attempt has been made in this work to determine the segregation characteristics of jetsam particles for both the homogeneous and heterogeneous binary mixtures in terms of segregation distance by correlating it to 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 and / or particle densities of the mixture through the dimensional analysis. Correlation on the basis of Artificial Neural Network approach has also been developed with the above system parameters so authenticating the development of correlation by the former approach. calculated values ​​of the segregation distance obtained for both homogeneous and heterogeneous binary mixtures from both the types of fluidized beds (ieunder the static be d condition and the fluidized bed condition) have also been compared with each other.