While much attention has been given to the development of computer techniques for design of distillation and absorption columns, much less attention has been devoted to the development of such techniques for equipment using liquid-liquid extraction. However, regardless of the nature of the operation, few systematic attempts have been made to organize phase-equilibrium information for direct use in chemical process design. This monograph presents a systematic procedure for calculating multi-component vapor-liquid and liquid-liquid equilibria for mixtures commonly encountered in the chemical process industries. Attention is limited to systems at low or moderate pressures. Pertinent references to previous work are given at the end of this chapter.  [c.1]

Kogan, V. B., V. M. Friedman, and V. V. Kafarov "Vapor-Liquid Equilibria," 2 vol., Nauka, Moscow, 1966.  [c.10]

We make the simplifying assumption that both and are functions only of temperature, not of pressure and composition. For a condensable component it follows that at the same tempera-ture, .  [c.22]

At pressures to a few bars, the vapor phase is at a relatively low density, i.e., on the average, the molecules interact with one another less strongly than do the molecules in the much denser liquid phase. It is therefore a common simplification to assume that all the nonideality in vapor-liquid systems exist in the liquid phase and that the vapor phase can be treated as an ideal gas. This leads to the simple result that the fugacity of component i is given by its partial pressure, i.e. the product of y, the mole fraction of i in the vapor, and P, the total pressure. A somewhat less restrictive simplification is the Lewis fugacity rule which sets the fugacity of i in the vapor mixture proportional to its mole fraction in the vapor phase the constant of proportionality is the fugacity of pure i vapor at the temperature and pressure of the mixture. These simplifications are attractive because they make the calculation of vapor-liquid equilibria much easier the K factors = i i  [c.25]

Witn the advent of electronic computers, it is no longer necessary to make drastic simplifying assumptions to reduce the  [c.25]

Much theoretical and experimental information is available  [c.28]

Bfi and 022- However, in the second binary, intermolecular forces between unlike molecules are much stronger than those between like molecules chloroform and ethyl acetate can strongly hydrogen bond with each other but only very weakly with them-  [c.31]

Figure 5 shows fugacity coefficients for the system acetaldehyde-acetic acid at 90°C and 0.25 atm. Calculations are based on the "chemical" theory of vapor imperfection. Although the pressure is far below atmospheric, fugacity coefficients for both components are well removed from unity. Because of strong dimerization between acetic acid molecules and weak dimerization between the other possible pairs, deviations from ideality are large, much larger than one might expect at this low pressure.  [c.34]

By contrast, in the system propionic acid d) - methyl isobutyl ketone (2), (fi and are very much different when y 1, Propionic acid has a strong tendency to dimerize with itself and only a weak tendency to dimerize with ketone also,the ketone has only a weak tendency to dimerize with itself. At acid-rich compositions, therefore, many acid molecules have dimerized but most ketone molecules are monomers. Acid-acid dimerization lowers the fugacity of acid and thus is well below unity. Because of acid-acid dimerization, the true mole fraction of ketone is signi-  [c.35]

Figure 5 shows the isothermal data of Edwards (1962) for n-hexane and nitroethane. This system also exhibits positive deviations from Raoult s law however, these deviations are much larger than those shown in Figure 4. At 45°C the mixture shown in Figure 5 is only 15° above its critical solution temperature. Again, representation with the UNIQUAC equation is excellent. Figure 5 shows the isothermal data of Edwards (1962) for n-hexane and nitroethane. This system also exhibits positive deviations from Raoult s law however, these deviations are much larger than those shown in Figure 4. At 45°C the mixture shown in Figure 5 is only 15° above its critical solution temperature. Again, representation with the UNIQUAC equation is excellent.
Since we make the simplifying assumption that the partial molar volumes are functions only of temperature, we assume that, for our purposes, pressure has no effect on liquid-liquid equilibria. Therefore, in Equation (23), pressure is not a variable. The activity coefficients depend only on temperature and composition. As for vapor-liquid equilibria, the activity coefficients used here are given by the UNIQUAC equation. Equation (15).  [c.63]

Liquid-liquid equilibria are much more sensitive than vapor-liquid equilibria to small changes in the effect of composition on activity coefficients. Therefore, calculations for liquid-liquid equilibria should be based, whenever possible, at least in part, on experimental liquid-liquid data.  [c.63]

For systems of type II, if the mutual binary solubility (LLE) data are known for the two partially miscible pairs, and if reasonable vapor-liquid equilibrium (VLE) data are known for the miscible pair, it is relatively simple to predict the ternary equilibria. For systems of type I, which has a plait point, reliable calculations are much more difficult. However, sometimes useful quantitative predictions can be obtained for type I systems with binary data alone provided that  [c.63]

Figure 15 shows results for a difficult type I system methanol-n-heptane-benzene. In this example, the two-phase region is extremely small. The dashed line (a) shows predictions using the original UNIQUAC equation with q = q. This form of the UNIQUAC equation does not adequately fit the binary vapor-liquid equilibrium data for the methanol-benzene system and therefore the ternary predictions are grossly in error. The ternary prediction is much improved with the modified UNIQUAC equation (b) since this equation fits the methanol-benzene system much better. Further improvement (c) is obtained when a few ternary data are used to fix the binary parameters.  [c.66]

Bryson, A. E., Ho, Y. B., "Applied Optimal Control Optimization, Estimation and Control," Blaisdell Publishing, Waltham, Mass. (1969).  [c.80]

In Equation (15), the third term is much more important than the second term. The third term gives the enthalpy of the ideal liquid mixture (corrected to zero pressure) relative to that of the ideal vapor at the same temperature and composition. The second term gives the excess enthalpy, i.e. the liquid-phase enthalpy of mixing often little basis exists for evaluation of this term, but fortunately its contribution to total liquid enthalpy is usually not large.  [c.86]

For many liquid mixtures. Equation (19) can be used to provide a crude estimate of excess enthalpy. A much better estimate is obtained if the UNIQUAC parameters are considered temperature-dependent. For example, suppose Equations (4-9) and (4-10) are modified to = + k /t  [c.87]

If this criterion is based on the maximum-likelihood principle, it leads to those parameter values that make the experimental observations appear most likely when taken as a whole. The likelihood function is defined as the joint probability of the observed values of the variables for any set of true values of the variables, model parameters, and error variances. The best estimates of the model parameters and of the true values of the measured variables are those which maximize this likelihood function with a normal distribution assumed for the experimental errors.  [c.98]

Bryson, A. E., Ho, Y. B., "Applied Optimal Control Optimization, Estimation, and Control," Blaisdell Publishing, Waltham, Mass. (1969).  [c.109]

A much preferable form of Equation (7-10) was described by Rach-ford and Rice (1952), who considered Equations (7-6) and (7-7) in the form  [c.113]

The procedure would then require calculation of (2m+2) partial derivatives per iteration, requiring 2m+2 evaluations of the thermodynamic functions per iteration. Since the computation effort is essentially proportional to the number of evaluations, this form of iteration is excessively expensive, even if it converges rapidly. Fortunately, simpler forms exist that are almost always much more efficient in application.  [c.117]



Once the flowsheet structure has been defined, a simulation of the process can be carried out. A simulation is a mathematical model of the process which attempts to predict how the process would behave if it was constructed (see Fig. 1.1b). Having created a model of the process, we assume the flow rates, compositions, temperatures, and pressures of the feeds. The simulation model then predicts the flow rates, compositions, temperatures, and pressures of the products. It also allows the individual items of equipment in the process to be sized and predicts how much raw material is being used, how much energy is being consumed, etc. The performance of the design can then be evaluated.  [c.1]

Building an irreducible structure. The first approach follows the onion logic, starting the design by choosing a reactor and then moving outward by adding a separation and recycle system, and so on. At each layer we must make decisions based on the information available at that stage. The ability to look ahead to the completed design might lead to different decisions. Unfortunately, this is not possible, and instead, decisions must be based on an incomplete picture.  [c.8]

The preference is for a process based on ethylene rather than the more expensive acetylene and chlorine rather than the more expensive hydrogen chloride. Electrolytic cells are a much more convenient and cheaper source of chlorine than hydrogen chloride. In addition, we prefer to produce no byproducts.  [c.17]

Having made a choice of the reaction path, we need to choose a reactor type and make some assessment of the conditions in the reactor. This allows assessment of reactor performance for the chosen reaction path in order for the design to proceed.  [c.18]

Because there are two feeds to this process, the reactor performance can be calculated with respect to both feeds. However, the principal concern is performance with respect to toluene, since it is much more expensive than hydrogen.  [c.25]

If selectivity increases as conversion increases, the initial setting for reactor conversion should he on the order of 95 percent, and that for reversible reactions should be on the order of 95 percent of the equilibrium conversion. If selectivity decreases with increasing conversion, then it is much more difficult to give guidance. An initial setting of 50 percent for the conversion for irreversible reactions or 50 percent of the equilibrium conversion for reversible reactions is as reasonable as can be guessed at this stage. However, these are only initial guesses and will almost certainly be changed later.  [c.27]

However, a note of caution should be added. In many multiphase reaction systems, rates of mass transfer between different phases can be just as important or more important than reaction kinetics in determining the reactor volume. Mass transfer rates are generally higher in gas-phase than liquid-phase systems. In such situations, it is not so easy to judge whether gas or liquid phase is preferred.  [c.45]

Unfortunately, despite much research into the fundamentals of catalysis, the choice of catalyst is still largely empirical. The catalytic process can be homogeneous or heterogeneous.  [c.46]

Catalytic gas-phase reactions play an important role in many bulk chemical processes, such as in the production of methanol, ammonia, sulfuric acid, and nitric acid. In most processes, the effective area of the catalyst is critically important. Since these reactions take place at surfaces through processes of adsorption and desorption, any alteration of surface area naturally causes a change in the rate of reaction. Industrial catalysts are usually supported on porous materials, since this results in a much larger active area per unit of reactor volume.  [c.47]

The secondary reactions are parallel with respect to ethylene oxide but series with respect to monoethanolamine. Monoethanolamine is more valuable than both the di- and triethanolamine. As a first step in the flowsheet synthesis, make an initial choice of reactor which will maximize the production of monoethanolamine relative to di- and triethanolamine.  [c.50]

Solution We wish to avoid as much as possible the production of di- and triethanolamine, which are formed by series reactions with respect to monoethanolamine. In a continuous well-mixed reactor, part of the monoethanolamine formed in the primary reaction could stay for extended periods, thus increasing its chances of being converted to di- and triethanolamine. The ideal batch or plug-flow arrangement is preferred, to carefully control the residence time in the reactor.  [c.50]

An initial guess for the reactor conversion is very difficult to make. A high conversion increases the concentration of monoethanolamine and increases the rates of the secondary reactions. As we shall see later, a low conversion has the effect of decreasing the reactor capital cost but increasing the capital cost of many other items of equipment in the flowsheet. Thus an initial value of 50 percent conversion is probably as good as a guess as can be made at this stage.  [c.51]

The accuracy of our calculations is strongly dependent on the accuracy of the experimental data used to obtain the necessary parameters. While we cannot make any general quantitative statement about the accuracy of our calculations for multicomponent vapor-liquid equilibria, our experience leads us to believe that the calculated results for ternary or quarternary mixtures have an accuracy only slightly less than that of the binary data upon which the calculations are based. For multicomponent liquid-liquid equilibria, the accuracy of prediction is dependent not only upon the accuracy of the binary data, but also on the method used to obtain binary parameters. While there are always exceptions, in typical cases the technique used for binary-data reduction is of some, but not major, importance for vapor-liquid equilibria. However, for liquid-liquid equilibria, the method of data reduction plays a crucial role, as discussed in Chapters 4 and 6.  [c.5]



The flowsheets shown in Fig. 1.3 feature the same reactor design. It could be useful to explore changes in reactor design. For example, the size of the reactor could be increased to increase the aunount of FEED which reacts (Fig. 1.4a). Now there is not only much less FEED in the reactor effiuent but more PRODUCT and BYPRODUCT. However, the increase in BYPRODUCT is larger than the increase in PRODUCT. Thus, although the reactor in Fig. 1.4a has the same three components in its effiuent as the reactor in Fig. 1.2a, there is less FEED, more PRODUCT, and significantly more BYPRODUCT. This change in reactor design generates a different task for the separation system, and it is possible that a separation system different from that shown in Figs. 1.2 and 1.3 is now appropriate. Figure 1.46 shows a possible alternative. This also uses two distillation columns, but the separations are carried out in a different order.  [c.4]

It is now possible to define the goals for the selection of the reactor at this stage in the design. Unconverted material usually can be separated and recycled later. Because of this, the reactor conversion cannot be fixed finally until the design has progressed much further than just choosing the reactor. As we shall see later, the choice of reactor conversion has a major influence on the rest of the process. Nevertheless, some decisions must be made regarding the reactor for the design to proceed. Thus we must make some guess for the reactor conversion in the knowledge that this is likely to change once more detail is added to the total system.  [c.25]

Clearly, in the liquid phase much higher concentrations of Cfeed (kmol m ) can be maintained than in the gas phase. This makes liquid-phase reactions in general more rapid and hence leads to smaller reactor volumes for liquid-phase reactors.  [c.45]

See pages that mention the term Mascia : [c.4]    [c.23]    [c.38]    [c.79]    [c.177]    [c.269]    [c.11]    [c.42]    [c.45]    [c.47]   
Practical aspects of finite element modelling of polymer processing (2002) -- [ c.189 ]