Fluidization viscosity

It can be seen from the above equations that the viscosity of the gas only becomes important at these low gas velocities for typical particle sizes which are used in fluidized beds. 

The bubble size at formation varied with particle characteristics. It was further observed that the bubble size decreased with increasing fluidization intensity (i.e., with increasing liquid velocity). The rate of coalescence likewise decreased with increasing fluidization intensity the net rate of coalescence had a positive value at distances from 1 to 2 ft above the orifice, whereas at larger distances from the orifice the rate approached zero. The bubble rise-velocity increased steadily with bubble size in a manner similar to that observed for viscous fluids, but different to that observed for water. An attempt was made to explain the dependence of the rate of coalescence on fluidization intensity in terms of a relatively high viscosity of the liquid fluidized bed. 

Observations of bubbles emerging through the bed surface show that bubble shape is markedly dependent on liquid velocity. This indicates the existence of a relationship between bed viscosity and liquid velocity. A bed near incipient fluidization is characterized by a high viscosity, and an emerging bubble is of nearly spherical shape, whereas a fluidized bed of high porosity is characterized by a viscosity not very much higher than that of water, so that an emerging bubble is of spherical cap shape. 

The fluidizing gas is usually methane, helium, or another non-reactive gas. Factors to consider to obtain proper fluidization are the density and size of the particles to be coated, and the velocity, density, and viscosity of the gases.If the velocity is too low, the particles will fall into the gas inlet if it is too high, they... 

In later sections, the use of the scaling relationships to design small scale models will be illustrated. For scaling to hold, all of the dimensionless parameters given in Eqs. (36), (37) or (39) must be identical in the scale model and the commercial bed under study. If the small scale model is fluidized with air at ambient conditions, then the fluid density and viscosity are fixed and it will be shown there is only one unique modeling condition which will allow complete similarity. In some cases this requires a model which is too large and unwieldy to simulate a large commercial bed. 

The simplified scaling relationships, Eq. (53), offer some flexibility in the model design since fewer parameters must be matched than with the full set of scaling relationships. When the fluidizing gas, the pressure and temperature of the scale model are chosen, the gas density and viscosity for the scale model are set. The model must still be geometrically similar to the commercial bed. There is still one free parameter. Generally this will be the linear scale of the model. For the simplified scaling relationships, the gas-to-solid density ratio must be maintained constant... 

Most fluidized-bed processes operate within the temperature and pressure ranges of ambient to 1100°C and ambient to 70 bar, respectively. Over this temperature range, gas viscosity increases by a factor of about 3 to 4, depending upon the type of gas. If the pressure of the system remains constant while temperature is changed, the gas density decreases over this temperature range by a factor of 1373/293 = 4.7. If system pressure is increased without changing temperature, the gas density is increased by the same factor as the pressure ratio—which would be approximately 70 1 for a change in pressure from ambient to 70 bar. 

The effects of temperature and pressure on fluidized-bed systems cannot be considered independently of particle size. Whether temperature and pressure have an effect (and indeed, even the direction of that effect) on a system, depends strongly on particle size. In addition, the type of interaction between gas and solids, i.e., whether the interaction is due to momentum or drag, determines if gas viscosity has an effect upon the system. As will be shown, gas viscosity is not important in systems in which momentum is important, but is important in systems dominated by drag. 

One of the strengths of the KTGF, although still under development, is that it can offer a very clear physical picture with respect to the key parameters (e.g., particle pressure, particle viscosity, and other transport coefficients) that are used in the TFMs. The TFMs based on KTGF requires less ad hoc adjustments compared to the other two types of models. Therefore, it is the most promising framework for modeling engineering-scale fluidized beds. 

An advantage of this approach to model large-scale fluidized bed reactors is that the behavior of bubbles in fluidized beds can be readily incorporated in the force balance of the bubbles. In this respect, one can think of the rise velocity, and the tendency of rising bubbles to be drawn towards the center of the bed, from the mutual interaction of bubbles and from wall effects (Kobayashi et al., 2000). In Fig. 34, two preliminary calculations are shown for an industrial-scale gas-phase polymerization reactor, using the discrete bubble model. The geometry of the fluidized bed was 1.0 x 3.0 x 1.0 m (w x h x d). The emulsion phase has a density of 400kg/m3, and the apparent viscosity was set to 1.0 Pa s. The density of the bubble phase was 25 g/m3. The bubbles were injected via 49 nozzles positioned equally distributed in a square in the middle of the column. 

Knowledge of the size and density of the particles to be fluidized, of the density and viscosity of the fluidizing gas (at the relevant... 

This equation allows the prediction of minimum fluidizing velocity from a knowledge of the mean particle diameter, the particle density, the density of fluidizing medium and fhe viscosity of fluidizing medium (SI units). Couderc (1985) quotes data which show that the inaccuracy of Leva s equation increases significantly outside the range 2 < Re < 30. 

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