Complex distillation processes examples

A separation process is sought that can satisfy both our present economic and enviromental constraints. It would also provide an alternative to present practice that relies on expensive azeotropic or extractive distillation processes used in the recovery of products from low relative volatility streams. As an example, virtually all industrial butadiene recovery processes now rely on extractive distillation using acetonitrile or other equivalent agent to enhance the relative volatility of the C4 components. The use of supercritical or near critical separation of these streams may satisfy these requirements provided certain pressure, temperature and recompression criteria can be met. Such a process would also reduce the need for a complex train of distillation towers. 

We first review in Part 1 the basics of plantwide control. We illustrate its importance by highlighting the unique characteristics that arise when operating and controlling complex integrated processes. The steps of our design procedure are described. In Part 2, we examine how the control of individual unit operations fits within the context of a plantwide perspective. Reactors, heat exchangers, distillation columns, and other unit operations are discussed. Then, the application of the procedure is illustrated in Part 3 with four industrial process examples the Eastman plantwide control process, the butane isomerization process, the HDA process, and the vinyl acetate monomer process. 

It is not difficult to observe that, in this example, we have the coupling of a specific reactor for petroleum fractionation together with a complex distillation column. If we intend to show the complexity of the process that will be simulated. 

A complex system is one containing so many components that they cannot be separated into discreet pure components by the distillation process. An example of such a system is naturally occurring petroleum, which contains hundreds of chemical constituents. Crude tall oil from paper pulping is another example of a complex system. 

Knowledge of the equilibrium is a fundamental prerequisite for the design of non-reactive as well as reactive distillation processes. However, the equilibrium in reactive distillation systems is more complex since the chemical equilibrium is superimposed on the vapor-liquid equilibrium. Surprisingly, the combination of reaction and distillation might lead to the formation of reactive azeotropes. This phenomenon has been described theoretically [2] and experimentally [3] and adds new considerations to feasibility analysis in RD [4]. Such reactive azeotropes cause the same difficulties and limitations in reactive distillation as azeotropes do in conventional distillation. On the basis of thermodynamic methods it is well known that feasibility should be assessed at the limit of established physical and chemical equilibrium. Unfortunately, we mostly deal with systems in the kinetic regime caused by finite reaction rates, mass transfer limitations and/or slow side-reactions. This might lead to different column structures depending on the severity of the kinetic limitations [5], However, feasibility studies should identify new column sequences, for example fully reactive columns, non-reactive columns, and/or hybrid columns, that deserve more detailed evaluation. 

The mass balances (Eqs. (10.3) and (10.4)) assume plug-flow behavior for both the vapor and the liquid phase. However, real flow behavior is much more complex and constitutes a fundamental issue in multiphase reactor design. It has a strong influence on the column performance, for example via backmixing of both phases, which is responsible for significant effects on the reaction rates and product selectivity. Possible development of stagnant zones results in secondary undesired reactions. To ensure an optimum model development for catalytic distillation processes, we performed experimental studies on the nonideal flow behavior in the catalytic packing MULTIPAK [77]. 

An example of an estimate of the total capital investment for a processing plant is given in Tables 16.14 and 16.15 for an ammonia plant producing 1 billion Ib/yr. The costs are for the year 2000 at a U.S. Midwest location. The plant is part of an integrated complex. The process involves a variety of equipment, including gas compressors, pumps, heat exchangers, a catalytic reactor, a distillation column, an absorber, a flash drum, a gas adsorber, and gas permeation membrane separators. The material of construction is almost exclusively carbon steel. 

The heterogeneous azeotropic distillation process provides an excellent example of the utility of distillation simulation to both design and control of a very complex nonideal system. 

Azeotropic distillation occurs when a mixture of two materials distils at constant composition. This technique is commonly used to remove water from samples. As an example, toluene may be added to a complex sample containing water, the distillation process results in the toluene-water... 

Susceptibility to aqueous cracking occurs to different degrees. Some alloys will break in moist air in the pre-cracked conditions, others require immersion in distilled water, while others require immersion in water containing appreciable amounts of dissolved halide. Different heat treatments may produce these different levels of susceptibility in one alloy. The Ti-8AI-1 Mo-1 V alloy, for example, will fail in laboratory air in the step-cooled condition, but requires immersion in distilled water in the mill-annealed condition and in 0.6 m KCl in the duplex annealed condition. Heat treatment of titanium alloys produces a variety of phase structures, morphology and composition, and the effects upon stress-corrosion susceptibility are complex. Generally, processes increasing the yield stress low A, c and A iscc> while... 

Petroleum fractions contain many different hydrocarbon molecules and ever more stringent environmental constraints now determine con iosition and purity requirements of the products. Furthermore, when upgrading different hydrocarbon streams the formation of side-products leads to even more complex mixtures. For example when producing linear olefinic hydrocarbons by paraffin dehydrogenation aromatic side-products are formed [28]. Often, alkane/alkene/aromatic hydrocarbon mixtures have to be separated. For the liquid phase separation of normal alkenes from n-alkene/n-alkane mixtures, the OLEX process was developed [2]. Also, the separation of alkane/alkene mixtures by adsorption via Ji-complexation has been extensively studied [29-31]. However, no industrial adsorptive separation processes are available for the separation of either alkanes or alkenes of different chain length. Rather, a downstream distillation section is used as to separate for exan5)le the linear aZp/jfl-olefins (C4-C10) produced by the AlphaSelect Process (IFP) [32]. 

Although Pd is cheaper than Rh and Pt, it is still expensive. In Pd(0)- or Pd(ll)-catalyzed reactions, particularly in commercial processes, repeated use of Pd catalysts is required. When the products are low-boiling, they can be separated from the catalyst by distillation. The Wacker process for the production of acetaldehyde is an example. For less volatile products, there are several approaches to the economical uses of Pd catalysts. As one method, an alkyldi-phenylphosphine 9, in which the alkyl group is a polyethylene chain, is prepared as shown. The Pd complex of this phosphine has low solubility in some organic solvents such as toluene at room temperature, and is soluble at higher temperature[28]. Pd(0)-catalyzed reactions such as an allylation reaction of nucleophiles using this complex as a catalyst proceed smoothly at higher temperatures. After the reaction, the Pd complex precipitates and is recovered when the reaction mixture is cooled. 

The second classification is the physical model. Examples are the rigorous modiiles found in chemical-process simulators. In sequential modular simulators, distillation and kinetic reactors are two important examples. Compared to relational models, physical models purport to represent the ac tual material, energy, equilibrium, and rate processes present in the unit. They rarely, however, include any equipment constraints as part of the model. Despite their complexity, adjustable parameters oearing some relation to theoiy (e.g., tray efficiency) are required such that the output is properly related to the input and specifications. These modds provide more accurate predictions of output based on input and specifications. However, the interactions between the model parameters and database parameters compromise the relationships between input and output. The nonlinearities of equipment performance are not included and, consequently, significant extrapolations result in large errors. Despite their greater complexity, they should be considered to be approximate as well. 

There are a variety of ways of accomplishing a particular unit operation. Alternative types of process equipment have different inherently safer characteristics such as inventory, operating conditions, operating techniques, mechanical complexity, and forgiveness (i.e., the process/unit operation is inclined to move itself toward a safe region, rather than unsafe). For example, to complete a reaction step, the designer could select a continuous stirred tank reactor (CSTR), a small tubular reactor, or a distillation tower to process the reaction. 

The reason for this is simple. If the reaction chemistry is not "clean" (meaning selective), then the desired species must be separated from the matrix of products that are formed and that is costly. In fact the major cost in most chemical operations is the cost of separating the raw product mixture in a way that provides the desired product at requisite purity. The cost of this step scales with the complexity of the "un-mixing" process and the amount of energy that must be added to make this happen. For example, the heating and cooling costs that go with distillation are high and are to be minimized wherever possible. The complexity of the separation is a function of the number and type of species in the product stream, which is a direct result of what happened within the reactor. Thus the separations are costly and they depend upon the reaction chemistry and how it proceeds in the reactor. All of the complexity is summarized in the kinetics. 

As mentioned earlier, a major cause of high costs in fine chemicals manufacturing is the complexity of the processes. Hence, the key to more economical processes is reduction of the number of unit operations by judicious process integration. This pertains to the successful integration of, for example, chemical and biocatalytic steps, or of reaction steps with (catalyst) separations. A recurring problem in the batch-wise production of fine chemicals is the (perceived) necessity for solvent switches from one reaction step to another or from the reaction to the product separation. Process simplification, e.g. by integration of reaction and separation steps into a single unit operation, will provide obvious economic and environmental benefits. Examples include catalytic distillation, and the use of (catalytic) membranes to facilitate separation of products from catalysts. 

Steam distillation is a process whereby organic liquids may be separated at temperatures sufficiently low to prevent their thermal decomposition or whereby azeotropes may be broken. Fats or perfume production are examples of applications of this technique. The vapour-liquid equilibria of the three-phase system is simplified by the usual assumption of complete immiscibility of the liquid phases and the validity of the Raoult and Dalton laws. Systems containing more than one volatile component are characterised by complex dynamics (e.g., boiling point is not constant). 

None of the alternative strategies for catalyst/product separation has yet reached the point where it can be commercialised for the rhodium catalysed hydroformyation of long chain alkenes and there are very few examples of commercialisation in any catalytic applications. Batch continuous processing with low pressure product distillation has been commercialised but the complexity of the system suggests that alternatives may be able to compete. 

Even if you were only half awake when you read the preeeding chapter, you should have recognized that the equations developed in the examples eonstituted parts of mathematical models. This chapter is devoted to more complete examples. We will start with simple systems and progress to more realistic and complex processes. The most complex example will be a nonideal, nonequimolal-overflow, multicomponent distillation column with a veiy large number of equations needed for a rigorous description of the system. 

Thirty years ago these computed variables were calculated using pneumatic devices. Today they are much more easily done in the digital control computer. Much more complex types of computed variables can now be calculated. Several variables of a process can be measured and all the other variables can be calculated from a rigorous model of the process. For example, the nearness to flooding in distillation columns can be calculated from heat input, feed flow rate, and... 

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