Hydrodynamics of a turbulent fluidized bed is studied by means of the concurrent application of fiber optic sensors It is observed that in the vicinity of the column wall there is a high bubble activity region. Low bubble activity and A temperature increase from 22 to 145°C results in a more homogeneous turbulent fluidized bed with smaller bubbles Mass transfer coefficients between bubble-emulsion (kbe) and bubble-annulus (kh) are evaluated. The dominant mass and a helium tracer. negative bubble velocities are reported for the dense phase near the column centre-line region. and more gas flowing through an expanded dense bed emulsion phase.transfer path was the one from the bubbles to the annular region with kba being several times greater than kbe.On a etudi6 I'hydrodynamique d'un lit fluidise turbulent au moyen de I'application simultanee de capteurs a fibres On a observe dans la region de la paroi de la colonne une zone de forte activite de bullage. Une faible activite de bullage Une augmentation de la temperature de 22 a 145°C rend le lit fluidise turbulent plus homogene avec des bulles plus (Nakajima et al., 1991). Thus, there is limited data on turbulent fluidized beds operated at conditions other than room temperature. Studies at more elevated temperatures and relatively low superficial gas velocities were mainly concerned with the effect of temperature on minimum fluidization velocity and bed voidage (Otake et al., 1975; Mii et al., 1973;Sishtla et al., 1986). Reactor size, in most of these studies, was limited to bench scale or laboratory scale units (Kai and Furusaki, 1985;Yamazaki et al., 1986;Cai et al., 1988; Hatate et al., 1988; Rapagna et al., 1994).Modelling of fluidized beds requires the use of data from bubble sensors and tracers. Ege et al. (1999, in through a gate valve (V4). This valve was used to adjust the air flow. Air, before being fed to the fluidized bed, was heated using an electrical oven (0). Conditions of the preheated air were selected to adjust the fluidized bed reactor temperature. Air exiting the oven expanded into a plenum chamber,

We conducted experiments to determine the physical processes involved at the inversion point of water-kerosene dispersions. In the course of these experiments, we noted a viscosity maximum at the inversion point. This led to the development of an indirect method for determining the viscosity of concentrated liquid dispersions. Our data were found to be best fit by the dispersion viscosity equation (eq 6). Dispersion viscosity expressed as a function of dispersed-phase volume fraction gives some insight into the structure of the dispersed phase near the inversion point.Liquid-liquid dispersions are used to promote heat and mass transfer in mixer-settler units. The phase inversion behavior of these dispersions is important since the drop size of the dispersed phase and the settling time of the dispersion depend on which of the phases is continuous.

One problem associated with the use of Computational Fluid Dynamics(CFD) in reactor modeling is the proper validation of the models. Proper validation in this context means that the physical fluid dynamic model, the mathematical implementation and the data used for validation must be consistent. The present paper addresses this issue and to provide appropriate relations between experimental method and modeling approach.A critical review of currently used measurement techniques for characterizing multiphase flow systems is presented. The interpretation of the data obtained from the various techniques is discussed as well as how these data can be used for validation of various CFD model formulations.Steady state models can be validated using time averaged data, making sure that the averaging time for the experimental data is long enough so that low frequency periodic oscillations also are evened out. If homogeneous systems are considered, then a volume average approach may be used for modeling. If the system cannot be considered homogeneous and steady, as is the most common case, then a dynamic ensemble averaging technique should be preferred. The validation of such models must be done with methods fast enough to resolve periodic fluctuating structures of interest. These methods are cumbersome and tedious to operate and the ergodic hypothesis may be invoked enabling the use of volume or time averaged data for the validation of ensemble averaged models.

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