Clusters identification and characterization in a gas–solid fluidized bed by the wavelet analysis

Abstract

The local solid flow structure of the bubbling fluidized bed of sand particles was investigated in order to identify and characterize the clusters. Extensive experiments were carried out using an optical fibre probe, measuring the velocity and the diameter of clusters. Under all operating conditions, ascending and descending clusters co-existed at all measurement locations. The locus of the inversion point at which the directions of cluster motion changed was determined. The velocity of the ascending clusters was a function of both superficial gas velocity and the radial and axial position. With increasing superficial gas velocity, both the velocity and the diameter of ascending clusters decreased near the wall. However, the velocity of descending clusters depended mainly on superficial gas velocity and the largest clusters existed closer to the wall. The results of this study help to explain cluster hydrodynamics in fluidized beds.On aétudié la structure locale de l'écoulement des solides dans un lit fluidisé bullant de particules de sable dans le but de déterminer et caractériser le phénomène d'agrégation. Des expériences approfondies ontété menéesà l'aide d'une sondeà fibres optiques, qui mesure la vitesse et le diamètre des agrégats. Les résultats montrent dans toutes les conditions opératoires la coexistence d'agrégats qui montent et qui descendent aux endroits où ontété prises les mesures. L'emplacement du point d'inversion où se produisent les changements de direction des agrégats aété déterminé. La vitesse des agrégats ascendants est fonctionà la fois de la vitesse de gaz superficielle et de la position tant radiale qu'axiale. Avec l'augmentation de la vitesse de gaz superficielle, la vitesse des agrégats ascendants diminue près des parois. La même tendance est observée pour le diamètre des agrégats ascendants. Toutefois, la vitesse des agrégats descendants dépend principalement de la vitesse de gaz superficielle et les plus gros agrégats se trouvent plutôt près des parois. Les résultats de cetteétude contribuentà la compréhension des agrégats dans les lits fluidisés.

Sequential modular simulation of circulating fluidized bed reactors

“…The existence of clusters in the riser has been experimentally observed by several researchers . When clusters are formed, two phases can be distinguished in each zone, encompassing a particle‐free gas phase and a particle‐rich cluster phase, similar to the particle‐free bubble phase and the particle‐rich emulsion phase in the traditional two‐phase model for the bubbling regime.…”

Effect of changes in particle size on the hydrodynamics of gas-solid fluidized beds through wall vibration

“…The second order Daubechies wavelet (DB2) was chosen as the mother wavelet for analysis of the vibration signals since it resulted in the minimum residual for a given order and scale among other mother wavelets tested [31,32]. The Shannon entropy was used to obtain the required level of decomposition and it was found that 9 levels of decomposition are enough for extracting all required information from the signal [33].…”

Multi‐scale analysis of acoustic emission signals in dense‐phase pneumatic conveying of pulverized coal at high pressure

“…Various techniques including pressure/differential pressure, electrostatic, optical fibers have been developed to analyze fluctuation signals and identify flow regimes or characterize the hydrodynamics in gas‐solid flows. However, due to the complex nature of gas‐solid two phase flow systems and various origins of the signals, valuable and meaningful information is very hard to obtain .…”

“…They further pointed out that multiscale resolution analysis method is a powerful tool to detect multiscale flow structures in gas‐solid flow such as bubbles, clusters, agglomerates and so on. Wavelet analysis method is often used to decompose the original fluctuation signals into different scales based on the frequency of each scale signals . Some researchers have divided the decomposed signals into three scales, namely, microscale, mesoscale, and macroscale signals.…”