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Characterization of fluidization regimes by analysis of pressure fluctuations in gas-solid fluidized beds.

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2017

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Fluidized beds are ranked as the top contacting method with the best overall benefits, and have been used over many years in several industrial applications. Literature indicates that pressure fluctuations are influenced by variables related to fluidization regimes in a fluidized bed; such as the bubble size, bubbling rising velocity and the motion of the bed surface (Fan et al., 1981). Hence several researchers have employed pressure fluctuations to aid in the understanding of fluidized bed system hydrodynamics. This study was focused on gas-solid fluidized beds, during aggregative fluidization represented by the bubbling, slugging and turbulent regimes. Geldart (1973) materials from the classification were studied in this research; Group A (spent Fluid Cracking Catalyst), Group B (sand) and Group D (plastic beads). The experimental equipment was composed of an existing laboratory-scale gas-solid fluidized bed and data acquisition system. Three transparent fluidized bed columns were investigated; fluidized bed 1 (I.D 5 cm), fluidized bed 2 (I.D 11 cm) and fluidized bed 3 (I.D 29 cm). The time-series analysis of pressure fluctuation signals were investigated using the time and frequency domain methods. The pressure fluctuation signal was converted into the frequency domain by use of the Fast Fourier Transform (FFT). For increased bed heights the power spectrum was narrower, higher in amplitude, had more distinct peaks and the dominant frequency was lower, when compared to the lower bed height for the same material and fluidization regime. Also decreasing dominant frequencies and large increases in the amplitude of the pressure fluctuation were observed for each increasing fluidization regime; from the bubbling to slugging and to the turbulent regimes. The research contribution from this study was realized, as a range of dominant frequencies were successfully identified for each specific fluidization regime at its respective velocities. The identification of the transition phase was accomplished with low accuracy from the research contribution. It was recommended to employ differential pressure measurements for larger columns to increase the accuracy of data achieved; thereby permitting the comparison of useable power spectra results for scale-up.

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Masters Degree (Chemical Engineering). University of KwaZulu-Natal. Durban, 2018.

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