Fluid velocity performance

Convection Heat Transfer. Convective heat transfer occurs when heat is transferred from a soHd surface to a moving fluid owing to the temperature difference between the soHd and fluid. Convective heat transfer depends on several factors, such as temperature difference between soHd and fluid, fluid velocity, fluid thermal conductivity, turbulence level of the moving fluid, surface roughness of the soHd surface, etc. Owing to the complex nature of convective heat transfer, experimental tests are often needed to determine the convective heat-transfer performance of a given system. Such experimental data are often presented in the form of dimensionless correlations. 

Mixer performance is often related in terms of the fluid velocity during agitation, total pumping capacity (flow of the fluid in the system) generated by one impeller, and the total flow in the tank (or sometimes as blending time or a solids-suspension criterion) [25]. 

Recently, studies were performed to quantitatively examine the hydrodynamics of the two most common in vitro dissolution testers. Rotational (tangential) fluid velocities were corre-... 

Extensive experiments were carried out to investigate the extrusion process. The first attempt to verify experimentally the flow rate equation for Newtonian fluids was made by Rowell and Finlayson [7]. The first experiments to verify the previously discussed velocity profiles for Newtonian fluids were performed by... 

One way that these operation regions can be identified to achieve optimization of the performance and productivity is through the use of contour plots derived directly from the experimental data for a particular polypeptide- or protein-ligate system as illustrated in Fig. 38. In this case, the optimization was based on a primary requirement of 94% yield. If a 60% column capacity utilization was the preferred option, the separation would have to be carried out in the region enclosed by the 94% yield curve and to the left of the 60% capacity curve. It can be seen that the highest production rate in the region occurs at the intersection of these two curves. Similar operational boundaries can be determined for the other cases, such as 70 or 50% as the preferred column capacities, and the values of fluid velocity and... 

The dimensionless term (9/u0 L, where 9 is the axial dispersion coefficient, u0 is the superficial fluid velocity, and L is the expanded-bed height) is the column-vessel dispersion number, Tc, and is the inverse of the Peclet number of the system. Two limiting cases can be identified from the axial dispersion model. First, when 9/u0L - 0, no axial dispersion occurs, while when 9/u0 L - 00 an infinite diffusivity is obtained and a stirred tank performance is achieved. The dimensionless term Fc, can thus be utilized as an important indicator of the flow characteristics within a fluidized-bed system.446... 

The separation was performed in a pilot test equipped with columns of 2.6 cm i.d. The first test was performed after a simple extrapolation of the parameters obtained for the calculation of the production scale unit (keeping the fluid velocity constant, Table 8). 

If recirculation rates are 10 to 15 times the feed rate, the reactor would tend to operate nearly isothermally. High velocities past the bed of particles could eliminate almost completely any external mass-transfer influence on the reactor performance. By varying the circulation rates, the reaction condition for which the mass transfer effect is negligible can be established. Except for the rapidly-decaying catalyst system, steady state can be achieved effectively. Sampling and product analysis can be obtained as effectively as in the fixed-bed reactor. Residence-time distributions for the fluid phases can be measured easily. High fluid velocities would cause less flow-maldistribution problems. 

Flow characteristics in a mixing vessel can influence process performance. The impeller is a device which imparts motion to the medium in which it operates. The characteristics of the flow which are of greatest interest are the mean fluid velocity at all points within the fluid and the turbulent fluctuations superimposed on the mean velocity. Paul and Treybal ( ) have discussed how the detailed flow characteristics can influence process performance. This paper will show how impeller style can influence the flow characteristics. 

We will use these data to obtain a general relationship between the pressure drop per unit height of packed bed and the other variables. To search for an actual solution to this problem, we begin by performing a dimensional analysis, which can be realized without any experiment. We wdll assume that the pressure drop per unit height of packed bed, Ap/H, is a function of the equivalent packed body diameter, d, the fluid density, p, the fluid viscosity, q, and the mean packed bed fluid velocity, w. 

Later Mayle, 1970 [400] continued their research by performing measurements of velocity and pressure within the fire whirl. He found that the behavior of the plume was governed by dimensionless plume Froude, Rossby, second Damkohler Mixing Coefficient and Reaction Rate numbers. For plumes with a Rossby number less than one the plume is found to have a rapid rate of plume expansion with height. This phenomenon is sometimes called vortex breakdown , and it is a hydraulic jump like phenomena caused by the movement of surface waves up the surface of the fire plume that are greater than the speed of the fluid velocity. Unfortunately, even improved entrainment rate type models do not predict these phenomena very well. 

Once the plant is accepted and fully operational, it becomes important to operate heat exchangers according to the conditions laid down in the design. Again attention to the temperature of operation and the fluid velocities is necessary to avoid accelerated fouling. Excursions of temperature particularly, even over short periods of time, may give rise to serious problems of deposits that are difficult to remove, affect performance, and are costly to remedy. Low velocity also may give rise to similar problems. 

The plug flow reactor is probably the most commonly used reactor in catalyst evaluation because it is simply a tube filled with catalyst that reactants are fed into. However, for catalyst evaluation, it is difficult to measure the reaction rate because concentration changes along the axis, and there are frequently temperature gradients, too. Furthermore, because the fluid velocity next to the catalyst is low, the chance for mass transfer limitations through the film around the catalyst is high. Eq. (3) is the reactor performance equation for a plug flow reactor. 

In practice, the fluid velocity profile is rarely flat, and spatial gradients of concentration and temperature do exist, especially in large-diameter reactors. Hence, the plug-flow reactor model (Fig. 7.1) does not describe exactly the conditions in industrial reactors. However, it provides a convenient mathematical means to estimate the performance of some reactors. As will be discussed below, it also provides a measure of the most efficient flow reactor—one where no mixing takes place in the reactor. The plug-flow model adequately describes the reactor operation when one of the following two conditions is satisfied ... 

The membrane separation plant is tubular ultraflltration (UF) and the pilot-plant operation was on a batch basis with a volume reduction factor approaching 40. The UF membrane had a maximum permeate flux of around 300 L/m hr at maximum 6 kg/cm inlet pressure and 3.8 m/s fluid velocity with a clean membrane. The flux typically dropped and approached 80 L/m hr at the end of a day s operation. The retentate from UF separation was returned to the feed tank whereas the permeate was routed to the sewer. Design of a full-scale plant was performed using a flux value of 40 L/m hr and volume reduction of 20x. 

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