Distillation flow parameter

For distillations, it is often of more interest to ascertain the effect of entrainment on efficiency than to predic t the quantitative amount of liquid entrained. For this purpose, the correlation shown in Fig. 14-26 is useful. The parametric curves in the figure represent approach to the entrainment flood point as measured or as predicted by Fig. 14-25 or some other flood correlation. The abscissa values are those of the flow parameter discussed earher. The ordinate values y are fractions of gross hquid downflow, defined as follows ... 

For preliminary design, liquid entrainment is usually used as a reference. To prevent entrainment, the vapor velocity for tray columns is usually in the range 1.5 to 3.5 ms-1. However, the entrainment of liquid droplets can be predicted using Equation 8.3 to calculate the settling velocity. To apply Equation 8.3 requires the parameter KT to be specified. For distillation using tray columns, KT is correlated in terms of a liquid-vapor flow parameter FLV, defined by ... 

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. 

Strigle (15) and Kister and Gill (60) compared predictions from the latest version of the Eckert correlation (Fig. 8.19a and b) to thousands of random packing pressure drop measurements. The Eckert correlation was shown to give good predictions for most pressure drop data (15,60). It generally works well for the alr-wator system for flow parameters as low as 0.01 and as high as 1 (60). For nonaqueous systems, it works well for flow parameters of 0.08 to 0.3 (typical of atmospheric distillation). 

The Eckert correlation was shown (60) to be optimistic for flow parameters greater than 0.3 (typical of pressure distillation and/or high liquid rate applications), Strigle (15) attributes thess optimistic pie-dictions to enhanced liquid frothiness at higher pressure. The ee-... 

For nonaqueous systems, the Eckert correlation is also optimistic for flow parameters lower than 0.03, which are typical of vacuum distillation and/or low liquid rates. Robbins (89) shows that the GPDC correlation use of liquid density and liquid viscosity is invalid at low flow parameters, where liquid properties should have little effect on pressure drop. It is worth noting that according to Robbins, this prediction difficulty is not unique to the Eckert correlation, but will be encountered whenever a correlation predicts a pressure drop dependence on liquid properties at low liquid rates. 

The calculation of column diameter for distillation and absorption columns %h,6 is usually based on the flooding velocity, which, in turn, requires values of the flooding capacity factor, Cf- Fair s flooding-capacity plot for sieve trays [1] correlates the flooding capacity factor with a flow parameter Flv for each tray-spacing value, t, as shown in Figure 2. The flow parameter involves the liquid mass flow, LMi, and vapor mass flow, F v (both in lb/ s), as well as the densities of the two streams. 

Flow parameters, X, from 0.05 to 0.3 give good fits. This is the normal operating range for atmospheric distillation systems. 

Process Studied. The numerical example used in this section with an aU-vapor distillate stream is a depropanizer with a feed that contains a small amount of ethane, but is mostly propane, isobutane, and -butane. Two cases are considered. The first has a feed composition that is 2mol% ethane and 40mol% propane, so the distillate flow rate is large and the RR is moderate (RR = 2.6). In the second case, the propane in the feed is only 4 mol% (with 0.02 mol% ethane), which gives a small vapor distillate flow rate and a large reflux ratio (RR = 20). Table 8.1 gives design parameters for the two cases. The Chao-Seader physical properties are used. 

Figure 10.1 gives the flowsheet and the steady-state parameters for the process. Note that the distillate flow rate is quite small because of the low concentration of DME in the feed. This gives a very high reflux ratio (RR = 41), which means that reflux-drum level will have to be controlled by manipulating reflux flow rate. 

D8. You have designed a sieve tray column with 0.4572 m tray spacing to operate at a pressure of 2.0 atm The value of the flow parameter is F/ = 0.5, and the flooding velocity was calculated as Uf]ood 1-83 m/s. Unfortunately, the latest lab results show that the distillation tenperature is too high and unacceptable thermal degradation occurs. To reduce the operating tenperature, you plan to reduce the column pressure to 0.5 atm Estimate the new flooding velocity. 

Experimental tests were carried out varying the operating parameters, like the concentration of As, the temperature (25-35°C) and the flow rate (100-250 Lh ) of the feed solution. The distillate flow rate was fixed at 100 L h"T Experimental tests have demonstrated that the value of flux did not depend on the As concentration and slightly increased with the feed flow rate. Table 13.5 shows a comparison among the transmembrane fluxes at three different feed temperatures, when the concentration of As(V) in the feed was 339 p,g L and feed flow rate was 100 L h. ... 

Flow parameter values from 0.04 to 0.17 are normal for atmospheric distillations. 

In addition, the experimental data indicate that the maximum value at constant flow parameter varies as the liquid viscosity to the —0.10 to —0.13 power. For liquid viscosities between 0.07 and 1.1 cps, an average of the —0.11 power of liquid viscosity can be used. Therefore, an ethanol/water distillation column would have a 3% lower maximum operational Q in the ethanol-rich rectifying section where the liquid viscosity is 0.39 cps than in the water-rich stripping section with a liquid viscosity of only 0.30 cps. Likewise, the data do not support an increase of more than 9% for the maximum operational Cs, as liquid viscosity is decreased below 0.20 cps. Equation 7-15 is used to calculate the maximum operational capacity for a particular service. 

Vapor/liquid equilibrium Flow parameter Mol fraction in liquid phase Mol fraction in bottoms liquid Mol fraction in distillate liquid Mol fraction in feed liquid Mol fraction heavy key in liquid Mol fraction light key in liquid Mol fraction in gas phase Relative volatility... 

The parameter q will be used to describe die thermal condidon of die feed. The rado of the internal reflux flow rate Lr to die distillate flow rate D is called the reflux rado R. 

Parameter Estimation Relational and physical models require adjustable parameters to match the predicted output (e.g., distillate composition, tower profiles, and reactor conversions) to the operating specifications (e.g., distillation material and energy balance) and the unit input, feed compositions, conditions, and flows. The physical-model adjustable parameters bear a loose tie to theory with the limitations discussed in previous sections. The relational models have no tie to theory or the internal equipment processes. The purpose of this interpretation procedure is to develop estimates for these parameters. It is these parameters hnked with the model that provide a mathematical representation of the unit that can be used in fault detection, control, and design. 

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