Distillation model

Costing investment analysis Data acquisition Database management Data conversion Development tools Dispersion models Distillation Drafting... 

Modelling a single tray is similar with a dynamic flash discussed before. The solution of the assembly of trays, increased with condenser, flash drum and reboiler, is a much more difficult problem, however. The equations presented below (for notations see Fig. 4.6) are known as MESH equations for modelling distillation columns at steady state enlarged with left hand terms for accumulation. 

Patil, P. MaMk, Z. Jobson, M. 2006, Prediction of CO2 and H2S SolubiUly in Aqueous MDEA Solutions Using an Extended Kent and Eisenberg Model Distillation and Absorption London, UK, 152,498-510. 

Pump and tank model Compressor model Heat exchanger model Cooling-tower model Steam-generation model Furnace model Distillation model Reaction model Separation model Absorption and stripping model Combination of the preceding models... 

Case Study 2 - Modelling distillation in work-up of Compound X... 

Just as interest in ethanol has driven the development of chemical models, distillation technology, and the field of metabolic engineering, it has also driven the development of the field of biomass deconstruction. Given that the focus of this book series is on biotechnology, this chapter will place more emphasis on the metabolic engineering aspect. However, key examples are briefly discussed in Section 18.3. 

Nitromethane is a very common material. Just go down to your local drag strip and pick up a gallon or two for doping your high performance cars fuel. It s also available up to 40% pure in RC model fuels. Simply fractionally distill the nitromethane (bp 101°C) out of the model fuel mixture and you re ready to go. If methanol Is present in the fuel formulation, some will azeotropically distill over with the nitromethane lowering its boiling point slightly, but this does not present a problem. 

The situation is very much poorer for stmctured rather than random packings, in that hardly any data on Hq and have been pubHshed. Based on a mechanistic model for mass transfer, a way to estimate HETP values for stmctured packings in distillation columns has been proposed (91), yet there is a clear need for more experimental data in this area. 

The important chemical properties of acetyl chloride, CH COCl, were described ia the 1850s (10). Acetyl chloride was prepared by distilling a mixture of anhydrous sodium acetate [127-09-3J, C2H202Na, and phosphorous oxychloride [10025-87-3] POCl, and used it to interact with acetic acid yielding acetic anhydride. Acetyl chloride s violent reaction with water has been used to model Hquid-phase reactions. 

Reactor types modeled A, stoichiometric conversion B, equiUbrium/free-energy minimization, continuous stirred tank, and plug flow C, reactive distillation. Some vendors have special models for special reactions also, private company simulators usually have reactors of specific interest to their company. 

General Properties of Computerized Physical Property System. Flow-sheeting calculations tend to have voracious appetites for physical property estimations. To model a distillation column one may request estimates for chemical potential (or fugacity) and for enthalpies 10,000 or more times. Depending on the complexity of the property methods used, these calculations could represent 80% or more of the computer time requited to do a simulation. The design of the physical property estimation system must therefore be done with extreme care. 

Distillation Columns. Distillation is by far the most common separation technique in the chemical process industries. Tray and packed columns are employed as strippers, absorbers, and their combinations in a wide range of diverse appHcations. Although the components to be separated and distillation equipment may be different, the mathematical model of the material and energy balances and of the vapor—Hquid equiUbria are similar and equally appHcable to all distillation operations. Computation of multicomponent systems are extremely complex. Computers, right from their eadiest avadabihties, have been used for making plate-to-plate calculations. 

Distillation appHcations can be characterized by the type of materials separated, such as petroleum appHcations, gas separations, electrolyte separations, etc. These appHcations have specific characteristics in terms of the way or the correlations by which the physical properties are deterrnined or estimated the special configurations of the process equipment such as having side strippers, multiple product withdrawals, and internal pump arounds the presence of reactions or two Hquid phases etc. Various distillation programs can model these special characteristics of the appHcations to varying degrees and with more or less accuracy and efficiency. 

Many industrial separations require a series of columns that are connected in specific ways. Some distillation programs can model such a system as a hypothetical single column with arbitrary cross-flows and connections and then carry out the distillation calculations for the modeled hypothetical column. Alternatively, such a system can be modeled as a process flow sheet using a process simulator. 

In using a spreadsheet for process modeling, the engineer usually finds it preferable to use constant physical properties, to express reactor performance as a constant "conversion per pass," and to use constant relative volatiHties for distillation calculations such simplifications do not affect observed trends in parametric studies and permit the user quickly to obtain useful insights into the process being modeled (74,75). 

In the chemical engineering domain, neural nets have been appHed to a variety of problems. Examples include diagnosis (66,67), process modeling (68,69), process control (70,71), and data interpretation (72,73). Industrial appHcation areas include distillation column operation (74), fluidized-bed combustion (75), petroleum refining (76), and composites manufacture (77). 

Differential-Algebraic Systems Sometimes models involve ordinary differentia equations subject to some algebraic constraints. For example, the equations governing one equihbrium stage (as in a distillation column) are... 

The second conversion of GS to (GSi)r will be Case 4 of Table 5-10, the two-surface-zone enclosure with computation simphfied by assuming that the direct-view fac tor from any spot to a surface equals the fraction of the whole enclosure that the surface occupies (the speckled-furnace model). This case can be considered an ideahzation of many processing furnaces such as distilling and cracking coil furnaces, with parts of the enclosure tube-covered and part left refrac-toiy. (But the refractory under the tubes is not to be classified as part of the refractory zone.) Again, one starts with substitution into Eq. (5-173) of the terms GSi, GS, and S Si from Table 5-10, Case 4, with all terms first converted to their gray-phis-clear form. To indicate the procedure, one of the components, S Si, wil be formulated. 

RGA Example In order to illustrate use of the RGA method, consider the following steady-state version of a transfer function model for a pilot-scale, methanol-water distillation column (Wood and Berry, Terminal Composition Control of a Binaiy Distillation Column, Chem. Eng. Sci, 28, 1707, 1973) Ku = 12.8, K = -18.9, K. i = 6.6, and Koo = —19.4. It follows that A = 2 and... 

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