Dysonian


Design of chemical processes almost always includes design for separation operations the most common of these are distillation, absorption, and extraction.  [c.1]

One of the essential ingredients for rational design of such separation operations is a knowledge of the required phase equilibria. The purpose of the present monograph is to present a technique, implemented for digital computers, to estimate these equilibria from a minimum of experimental information.  [c.1]

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]

Gmehling, J., and U. Onken "Vapor-Liquid Equilibrium Data Collection," DECHEMA Chemistry Data Ser., Vol. 1 (1-10), Frankfurt, 1977.  [c.8]

Design," Wiley-Interscience, New York, 1970.  [c.11]

The critical temperature of methane is 191°K. At 25°C, therefore, the reduced temperature is 1.56. If the dividing line is taken at T/T = 1.8, methane should be considered condensable at temperatures below (about) 70°C and noncondensable at higher temperatures. However, in process design calculations, it is often inconvenient to switch from one method of normalization to the other. In this monograph, since we consider only equilibria at low or moderate pressures in the region 200-600°K, we elect to consider methane as a noncondensable component.  [c.59]

In Equation (24), a is the estimated standard deviation for each of the measured variables, i.e. pressure, temperature, and liquid-phase and vapor-phase compositions. The values assigned to a determine the relative weighting between the tieline data and the vapor-liquid equilibrium data this weighting determines how well the ternary system is represented. This weighting depends first, on the estimated accuracy of the ternary data, relative to that of the binary vapor-liquid data and second, on how remote the temperature of the binary data is from that of the ternary data and finally, on how important in a design the liquid-liquid equilibria are relative to the vapor-liquid equilibria. Typical values which we use in data reduction are Op = 1 mm Hg, = 0.05°C, = 0.001, and = 0.003  [c.68]

Null, H. R., "Phase Equilibrium in Process Design," John Wiley, New York (19 70).  [c.80]

In modern separation design, a significant part of many phase-equilibrium calculations is the mathematical representation of pure-component and mixture enthalpies. Enthalpy estimates are important not only for determination of heat loads, but also for adiabatic flash and distillation computations. Further, mixture enthalpy data, when available, are useful for extending vapor-liquid equilibria to higher (or lower) temperatures, through the Gibbs-Helmholtz equation.  [c.82]

While many methods for parameter estimation have been proposed, experience has shown some to be more effective than others. Since most phenomenological models are nonlinear in their adjustable parameters, the best estimates of these parameters can be obtained from a formalized method which properly treats the statistical behavior of the errors associated with all experimental observations. For reliable process-design calculations, we require not only estimates of the parameters but also a measure of the errors in the parameters and an indication of the accuracy of the data.  [c.96]

In many process-design calculations it is not necessary to fit the data to within the experimental uncertainty. Here, economics dictates that a minimum number of adjustable parameters be fitted to scarce data with the best accuracy possible. This compromise between "goodness of fit" and number of parameters requires some method of discriminating between models. One way is to compare the uncertainties in the calculated parameters. An alternative method consists of examination of the residuals for trends and excessive errors when plotted versus other system variables (Draper and Smith, 1966). A more useful quantity for comparison is obtained from the sum of the weighted squared residuals given by Equation (1).  [c.107]

The most frequent application of phase-equilibrium calculations in chemical process design and analysis is probably in treatment of equilibrium separations. In these operations, often called flash processes, a feed stream (or several feed streams) enters a separation stage where it is split into two streams of different composition that are in equilibrium with each other.  [c.110]

Null, H. R., "Phase Equilibria in Process Design," Wiley-Interscience (1970).  [c.128]

Smith, B. D., "Design of Equilibrium Stage Processes," McGraw-Hill, New York (1963).  [c.129]

The Hierarchy of Chemical Process Design  [c.1]

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]

Once the basic performance of the design has been evaluated, changes can be made to improve the performance in other words, we optimize. These changes might involve the synthesis of alternative structures, i.e., structural optimization. Thus we simulate and  [c.2]

The Hierarchy of Chemical Process Design 3  [c.3]

This text will attempt to develop an understanding of the concepts required at each stage during the creation of a chemical process design.  [c.3]

Overall Process Design  [c.3]

The Hierarchy of Chemical Process Design 5  [c.5]

The Hierarchy of Process Design and the Onion Model  [c.5]

Our attempt to develop a methodology will be helped if we have a clearer picture of the structure of the problem. If the process requires a reactor, this is where the design starts. This is likely to be the only  [c.5]

The Hierarchy of Chemical Process Design 7  [c.7]

The hierarchical nature of process design has been represented in different ways by different authors. A hierarchy of decisions and a process design ladder also have been suggested.  [c.7]

The synthesis of the correct structure and the optimization of parameters in the design of the reaction and separation systems are often the single most important tasks of process design. Usually there are many options, and it is impossible to fully evaluate them unless a complete design is furnished for the outer layers of the onion. For example, it is not possible to assess which is better.  [c.7]

Later in this text an approach is presented in which some early decisions (i.e., decisions regarding reactor and separator options) can be evaluated without a complete design for the outer layers.  [c.8]

Approaches to Process Design  [c.8]

In broad terms, there are two approaches to chemical process design  [c.8]

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 Hierarchy of Chemical Process Design 9  [c.9]

The main advantage of this approach is that the designer can keep control of the basic decisions and interact with the design as it develops. By sta dng in control of the basic decisions, the intangibles of the design can be included in the decision making.  [c.9]

Creating and optimizing a reducible structure. In this approach, a structure known as a superstructure or hyperstructure is first created that has embedded within it all feasible process operations and all feasible interconnections that are candidates for an optimal design. Initially, redundant features are built into the structure. As an example, consider Fig. 1.7. This shows one possible structure of a process for the manufacture of benzene from the reaction between toluene and hydrogen. In Fig. 1.7, the hydrogen enters the process with a small amount of methane as an impurity. Thus in Fig. 1.7 the option is embedded of either purifying the hydrogen feed with a membrane or passing directly to the process. The hydrogen and toluene are mixed and preheated to reaction temperature. Only a furnace has been considered feasible in this case because of the high temperature required. Then two alternative reactor options, isothermal and adiabatic reactors, are embedded, and so on. Redundant features have been included in an effort to ensure that all features that could be part of an optimal solution haVe been included.  [c.9]

The Hierarchy of Chemical Process Design 11  [c.11]

Once the problem is formulated mathematically, its solution is carried out through implementation of an optimization algorithm. Economic potential is maximized or cost is minimized (see App. A) in a structural and parameter optimization. Should an integer variable be optimized to zero, the corresponding feature is deleted from the structure and the structure is reduced in complexity. In effect, the discrete decision-making aspects of process design are replaced by a discrete/continuous optimization. Thus the initial structure in Fig. 1.7 is optimized to reduce the structure to the final design shown in Fig. 1.8. In Fig. 1.8, the membrane separator on the hydrogen feed has been removed by optimization, as have the isothermal reactor and many other features of the initial structure shown in Fig. 1.7.  [c.11]

The Hierarchy of Chemical Process Design 13  [c.13]

On the other hand, this approach has a number of advantages. Many different design options can be considered at the same time. Also, the entire design procedure can be accommodated in a computer program capable of producing designs quickly and efficiently.  [c.13]

In summary, the two general approaches to chemical process design of building an irreducible structure and creating and optimizing a reducible structure both have advantages and disadvantages. Whichever is used in practice, however, there is no substitute for understanding the problem.  [c.13]

Figure 1.2 Process design starts with the reactor. The reactor design dictates the separation and recycle problem. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.) Figure 1.2 Process design starts with the reactor. The reactor design dictates the separation and recycle problem. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.)
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]

Figure 1.3 For a given reactor and separator design, there are different possibilities for heat integration. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.) Figure 1.3 For a given reactor and separator design, there are different possibilities for heat integration. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.)
Of course, some processes do not require a reactor, e.g., some oil refinery processes. Here, the design starts with the sepauration system and moves outward to the heat exchanger network and utilities. However, the basic hierarchy prevails.  [c.6]

Figure 1.5 A different reactor design leads not only to a different separation system but also to additional possibilities for heat integration. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.) Figure 1.5 A different reactor design leads not only to a different separation system but also to additional possibilities for heat integration. (From Smith and Linnhoff, Trans. IChemE, ChERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.)
Figure 1.6 The onion model of process design. A reactor design is needed before the separation ind recycle system can be designed, and so on. (From Smith and Linnhoff, Trans. IChemE, CkERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.) Figure 1.6 The onion model of process design. A reactor design is needed before the separation ind recycle system can be designed, and so on. (From Smith and Linnhoff, Trans. IChemE, CkERD, 66 195, 1988 reproduced by permission of the Institution of Chemical Engineers.)
The design problem is next formulated as a mathematical problem with design equations and design variables. The design equations are the modeling equations of the units and their specification constraints. Design variables are of two types. The first t3qje of design variables describe the operation of each unit (flow rate, composition, temperature, and pressure), its size (volume, heat transfer area, etc.), as well as the costs or profits associated with the units. Since  [c.9]


See pages that mention the term Dysonian : [c.2]    [c.6]    [c.9]    [c.9]    [c.11]    [c.11]   
The science and technology of carbon nanotubes (1999) -- [ c.85 ]