Pressure drop Resistance coefficient

The term essentially a drag coefficient for the dust cake particles, should be a function of the median particle size and particle size distribution, the particle shape, and the packing density. Experimental data are the only reflable source for predicting cake resistance to flow. Bag filters are often selected for some desired maximum pressure drop (500—1750 Pa = 3.75-13 mm Hg) and the cleaning interval is then set to limit pressure drop to a chosen maximum value. 

Flow coefficients (not resistance) for valves are generally available from the manufacturer. The coefficient of a valve is defined as tlie flow of water at 60°F, in gallons per minute, at a pressure drop of one pound per square inch across the valve [3], regardless of whether the valve ultimately will be flowing liquid or gases/vapors in the plant process. It is expressed ... 

Conditioned fabric maintains a relatively consistent dust-load deposit following a number of filtration and cleaning cycles. K may be more than 10 times the value of the resistance coefficient for the original clean fabric. If the depth of the dust layer on the fabric is greater than about inch (which corresponds to a fabric dust loading on the order of 0.1 Ibm/ft ), the pressure drop across the fabric, including the dust in the pores, is usually negligible relative to that across the dust layer alone. 

The Poppe plot is a log-log plot of H/uq = t(JN versus the number of plates with different particle sizes and with lines drawn at constant void time, t(). H is the plate height, Vis the number of plates, and u() is the fluid velocity (assumed equal to the void velocity). The quantity H/u() is called the plate time, which is the time for a theoretical plate to develop and is indicative of the speed of the separation, with units of seconds. In the Poppe plot, a number of parameters including the maximum allowable pressure drop, particle diameter, viscosity, flow resistance, and diffusion coefficient are held constant. 

For nebulizers and MDIs, the external resistance (Re) is quite low. Different approaches have been made to describe the external airflow resistance of DPIs. Olsson and Asking [99] derived an empirical relationship between flow rate () and pressure drop (AR), AR = for a number of inhalers (such as Rotahaler , Spinhaler and Turbuhaler ) in which they define the proportionality coefficient (C) as the airflow resistance. This relationship differs only slightly from the general (theoretical) equation for orifice types of flow constrictions ... 

As can be seen from the table, the mass flow rate ratio m m, has no effect on -Apim, and the equivalent local resistance coefficient jm calculated with Eq. (4.13) is essentially kept constant. This implies that the pressure drop across the impingement zone is independent of the presence of particles. The value for averaged over a total of 490 sets of data is equal to 0.096. So, the pressure drop across the impingement zone can be calculated with the relationship below ... 

Bar and Tamir [63] studied the two-impinging stream dryer with two pairs of airfeeding tubes, as briefly shown in Fig. 6.7. The purpose of adding the lower two air streams is to increase the hold-up and the mean residence time of the particles in the dryer, and also aims to enhance the turbulence between phases in order to increase the drying intensity. However, the experiments did not show that the secondary air streams increased either the hold-up or the transfer coefficient. On the other hand, the induction of the two secondary air streams results in the greatly increased hydraulic resistance of the system. The pressure drop across the dryer, with two pairs of air-feeding tubes and with a volume treble that of the dryer shown in Fig. 6.6, is as high as 3800 Pa. 

It is important to have the correct set of variables specified as independent and dependent to meet the modeling objectives. For monitoring objectives observed conditions, including the aforementioned independent variables (FICs, TICs, etc.) and many of the "normally" (for simulation and optimization cases) dependent variables (FIs, TIs, etc.) are specified as independent, while numerous equipment performance parameters are specified as dependent. These equipment performance parameters include heat exchanger heat transfer coefficients, heterogeneous catalyst "activities" (representing the relative number of active sites), distillation column efficiencies, and similar parameters for compressors, gas and steam turbines, resistance-to-flow parameters (indicated by pressure drops), as well as many others. These equipment performance parameters are independent in simulation and optimization model executions. 

In many industrial reactions, the overall rate of reaction is limited by the rate of mass transfer of reactants and products between the bulk fluid and the catalytic surface. In the rate laws and cztalytic reaction steps (i.e., dilfusion, adsorption, surface reaction, desorption, and diffusion) presented in Chapter 10, we neglected the effects of mass transfer on the overall rate of reaction. In this chapter and the next we discuss the effects of diffusion (mass transfer) resistance on the overall reaction rate in processes that include both chemical reaction and mass transfer. The two types of diffusion resistance on which we focus attention are (1) external resistance diffusion of the reactants or products between the bulk fluid and the external smface of the catalyst, and (2) internal resistance diffusion of the reactants or products from the external pellet sm-face (pore mouth) to the interior of the pellet. In this chapter we focus on external resistance and in Chapter 12 we describe models for internal diffusional resistance with chemical reaction. After a brief presentation of the fundamentals of diffusion, including Pick s first law, we discuss representative correlations of mass transfer rates in terms of mass transfer coefficients for catalyst beds in which the external resistance is limiting. Qualitative observations will bd made about the effects of fluid flow rate, pellet size, and pressure drop on reactor performance. 

Pilot plant smdied have also been performed by Larsen et al. [37], who obtained stable operation and more than 95% SO2 removal from flue gas streams with a gas-side pressure drop of less than 1000 Pa. The importance of the membrane structure on the SO2 removal has been studied by Iversen et al. [6], who calculated the influence of the membrane resistance on the estimated membrane area required for 95% SO2 removal from a coal-fired power plant. Authors performed experiments on different hydrophobic membranes with sodium sulfite as absorbent to measure the SO2 flux and the overall mass-transfer coefficient. The gas mixture contained 1000 ppm of SO2 in N2. For the same thickness, porosity, and pore size, membranes with a structure similar to random spheres (typical of stretched membranes) showed a better performance than those with a closely packed spheres stmcture. 

The adsorbent particles are normally used as beads, extrudates, or granules (-0.1 -0.3 cm equivalent diameters) in conventional H2 PSA processes. The particle diameters can be further reduced to increase the feed gas impurity mass transfer rates into the adsorbent at the cost of increased column pressure drop, which adversely affects the separation performance. The particle diameters, however, cannot be reduced indefinitely and adsorption kinetics can become limiting for very fast cycles48 New adsorbent configurations that offer (i) substantially less resistance to gas flow inside an adsorber and, thus, less pressure drop (ii) exhibit very fast impurity mass transfer coefficients and (iii) minimize channeling are the preferred materials for RPSA systems. At the same time, the working capacity of the material must be high and the void volume must be small in order to minimize the adsorber size and maximize the product recovery. Various materials satisfy many of the requirements fisted above, but not all of them simultaneously. 

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