Prediction of Spout Diameter in Gas-Solid Spouted Beds using Factorial Design of Experiments Approach with the Aid of Advanced Optical Fibre Probe
In this study, the effects of five operating and design variables (solid density, static bed height, particle diameter, superficial gas velocity, and inlet diameter) on the average spout diameter of a 0.152 m inside diameter gas-solid spouted bed have been assessed experimentally using advanced gas-solid optical fibre probe technique. Statistical analysis of the experimental data including the factorial design of the experiments using MINITAB17 statistical software has been performed to determine the extent of the effects of these variables on the spout diameter as a case study. It was found that all five operating and design variables, except the solid density together with the 2-ways interactions between particles size and inlet diameter, in addition to gas velocity and inlet diameter, have a significant effect on the average spout diameter. Regression analysis was performed to correlate these variables with the average spout diameter for the gas-solid spouted beds. The obtained preliminary regression correlation was able to closely predict the average spout diameter of this work with the mean relative deviation value of 0.7 %.
M. H. Al-Dahhan et al., "Prediction of Spout Diameter in Gas-Solid Spouted Beds using Factorial Design of Experiments Approach with the Aid of Advanced Optical Fibre Probe," Canadian Journal of Chemical Engineering, vol. 95, no. 8, pp. 1463-1470, Canadian Society for Chemical Engineering, Aug 2017.
The definitive version is available at https://doi.org/10.1002/cjce.22817
Chemical and Biochemical Engineering
Keywords and Phrases
Design of Experiments; Fluidized Beds; Gases; Optical Fibers; Probes; Regression Analysis; Average Spout Diameter; Design Variables; Optical Fibre Probes; Particle Diameters; Relative Deviations; Spouted Bed; Statistical Software; Superficial Gas Velocities; Statistical Methods; Gas-Solid Spouted Bed; Operating and Design Variables; Statistical Analysis
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Canadian Society for Chemical Engineering, All rights reserved.
01 Aug 2017