Energy of Power Spectral Density Function and Wavelet Analysis of Absolute Pressure Fluctuation Measurements in Fluidized Beds

Shou, M.C.; Leu, Lii-Ping

doi:10.1205/cherd.04123

Cited by 55 publications

(24 citation statements)

References 19 publications

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“…An expanded top section made of stainless steel is 1.5 m in height, with five times the cross-sectional area of riser bed as employed by Shou and Leu. 22 A perforated plate, distributed with 250 holes of 1.5-mm dia., giving an open-area ratio of 4.8 % is used as the gas distributor. Ambient air is supplied by a Roots blower to fluidize the particles.…”

Section: Methodsmentioning

confidence: 99%

Multiresolution analysis on identification and dynamics of clusters in a circulating fluidized bed

Yang

Leu

2009

AIChE Journal

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). An appropriate level of approximation subsignal was systematically specified as a threshold for cluster identification, based on multiresolution analysis (MRA) of wavelet transformation. By the established threshold, the dynamic properties of clusters including the appearance time fraction of clusters F cl , average cluster duration time s cl , cluster frequency f cl , and local average solids holdup in clusters e sc , at different radial and axial positions were determined under the turbulent, transition and fast fluidization flow regimes. The results also describe the dynamic properties of clusters and flow patterns in the splash zone along with the dense bottom region of the circulating fluidized beds.

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Section: Methodsmentioning

confidence: 99%

Multiresolution analysis on identification and dynamics of clusters in a circulating fluidized bed

Yang

Leu

2009

AIChE Journal

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“…Although the fluidization appears to be a random phenomenon, it constitutes periodical behavior locally and globally [14,15]. One way to identify flow condition in fluidization systems is to use their stochastic characteristics such as pressure and density [1,16].…”

Section: Introductionmentioning

confidence: 99%

Application of Scaling-Law and CFD Modeling to Hydrodynamics of Circulating Biomass Fluidized Bed Gasifier

et al. 2016

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Two modeling approaches, the scaling-law and CFD (Computational Fluid Dynamics) approaches, are presented in this paper. To save on experimental cost of the pilot plant, the scaling-law approach as a low-computational-cost method was adopted and a small scale column operating under ambient temperature and pressure was built. A series of laboratory tests and computer simulations were carried out to evaluate the hydrodynamic characteristics of a pilot fluidized-bed biomass gasifier. In the small scale column solids were fluidized. The pressure and other hydrodynamic properties were monitored for the validation of the scaling-law application. In addition to the scaling-law modeling method, the CFD approach was presented to simulate the gas-particle system in the small column. 2D CFD models were developed to simulate the hydrodynamic regime. The simulation results were validated with the experimental data from the small column. It was proved that the CFD model was able to accurately predict the hydrodynamics of the small column. The outcomes of this research present both the scaling law with the lower computational cost and the CFD modeling as a more robust method to suit various needs for the design of fluidized-bed gasifiers.

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“…Many investigators have used pressure signals [1,2] and their fluctuations to determine and distinguish between phenomena occurring within the bed like formation, movement, coalescence and break-up of bubbles, slugging etc. [3][4][5][6]. Various analysis methods of the pressure signals have been developed, for both time and frequency domains, such as wavelet analysis, Fourier transform, chaos analysis etc., to extract the necessary information about the hydrodynamic behavior of the fluidized bed, namely minimum fluidization velocity, regime transition velocities, bubble characteristics or to estimate the dominant phenomena in the bed [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Wavelet transform analysis was utilized for non-linear and transient time series data for a better resolution in the frequency domain [9]. For example, this method can be used to characterize regime transition from minimum fluidization to bubbling and from bubbling to turbulent fluidization [9].…”

Section: Introductionmentioning

confidence: 99%

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Effect of internal tubes on the flow structures in gas-solid fluidized beds

Gubis

Norouzi

Mostoufi

et al. 2013

J. Phys.: Conf. Ser.

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Abstract. The influence of internal tubes present in the fluidized bed on its hydrodynamic behavior was examined in this study. One tube was completely immersed in the bed of 650 m glass beads at 10 cm above the air distributor in the 15 cm inner diameter fluidized bed column of aspect ratio 1. The pressure fluctuations signal was collected over 300 s and was consequently analyzed by the both statistical and wavelet analyses. The results showed that the presence of tube within the bed suppresses the occurrence of macro-scale phenomena like formation of large bubbles and its stability and supports the meso-structures such smaller bubbles, voids and clusters. It leads to an earlier onset of bubbling flow regime as well as turbulent flow regime. The observed minimum bubbling velocities were compared with data in literature and were found in a good agreement with them.

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Energy of Power Spectral Density Function and Wavelet Analysis of Absolute Pressure Fluctuation Measurements in Fluidized Beds

Cited by 55 publications

References 19 publications

Multiresolution analysis on identification and dynamics of clusters in a circulating fluidized bed

Multiresolution analysis on identification and dynamics of clusters in a circulating fluidized bed

Application of Scaling-Law and CFD Modeling to Hydrodynamics of Circulating Biomass Fluidized Bed Gasifier

Effect of internal tubes on the flow structures in gas-solid fluidized beds

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