Extraction process behavioral model

Effect of Unlike-Pair Interactions on Phase Behavior. No adjustment of the unlike-pair interaction parameter was necessary for this system to obtain agreement between experimental data and simulation results (this is, however, also true of the cubic equation-of-state that reproduces the properties of this system with an interaction parameter interesting question that is ideally suited for study by simulation is the relationship between observed macroscopic phase equilibrium behavior and the intermolecular interactions in a model system. Acetone and carbon dioxide are mutually miscible above a pressure of approximately 80 bar at this temperature. Many systems of interest for supercritical extraction processes are immiscible up to much higher pressures. In order to investigate the transition to an immiscible system as a function of the strength of the intermolecular forces, we performed a series of calculations with lower strengths of the unlike-pair interactions. Values of - 0.90, 0.80, 0.70 were investigated. 

The value of the monomer partition coefBcient between the CO2 and the water phase indirectly determines the ratio between the effect of enhanced polymerization and the effect of extraction on the reduction of residual monomer. Depending on the process conditions, i.e. temperature, pressure, and the phase behavior of the system involved, this ratio between enhanced polymerization and extraction may vary for different latex systems. With respect to the PMMA latex, the high partition coefBcient m2 as shown in Section 14.4, causes extraction to be the predominant effect as compared to conversion of the monomer. Therefore, a preliminary process design has been developed based on C02-extraction. For this purpose, a mass transfer model has been set up to determine the rate-limiting step in the extraction process. In addition, a process flow diagram, including equipment sizing has been developed. Finally, an economic evaluation has been performed to study the viability of this technique for the removal of residual monomer from latex-products. 

Models can be categorized in various ways. Predictive models forecast the future behavior of a system, whereas conceptual models are used to understand relationships between system parts and processes. Deterministic models are constructed from mathematical functions that imambiguously relate cause and effect so that a particular set of input parameters produces a clearly related set of predicted results. Probabilistic models use statistical data to estimate the chance that an event or condition will occur. Forward models predict the future behavior of a system, whereas inverse (or reverse) models are used to extract fundamental data or mathematical relationships from past observations. 

Liquid-liquid equilibrium (LEE) data of ternary systems are required for the design of liquid extraction processes. Also, there is a constant need for phase equilibrium data of these systems for simulation and optimize of separation equipment, valuable information about the molecular interactions, macroscopic behavior of fluid ntixtures, and can be used to test and improve thermodynamic models for calculating and predicting fluid-phase equilibria. 

Ethyl-lactate is a novel ecofriendly solvent with potential applications in supercritical fluid technology, as a co-solvent of earbon dioxide, in high pressiue chemical reactions, supercritical extraction processes and/or anti-solvent precipitation processes. In view of this, knowledge of the phase behavior of (ethyl lactate + CO2) binary is essential for the modeling and design of sueh proeesses. 

The model, therefore, predicts the elution behavior of solutes during a chromatographic process over a swollen gel as the stationary phase as a function of solute size and of the gel nanomorphology. On the reverse, from the elution behavior of solutes of known molecular size it is possible to extract the polymer chain concentration from chromatographic experiments, where an unknown swollen gel is the stationary phase. This is the basis of the ISEC, which is so often mentioned through this chapter [16,17,105,106]. 

As discussed and illustrated in the introduction, data analysis can be conveniently viewed in terms of two categories of numeric-numeric manipulation, input and input-output, both of which transform numeric data into more valuable forms of numeric data. Input manipulations map from input data without knowledge of the output variables, generally to transform the input data to a more convenient representation that has unnecessary information removed while retaining the essential information. As presented in Section IV, input-output manipulations relate input variables to numeric output variables for the purpose of predictive modeling and may include an implicit or explicit input transformation step for reducing input dimensionality. When applied to data interpretation, the primary emphasis of input and input-output manipulation is on feature extraction, driving extracted features from the process data toward useful numeric information on plant behaviors. 

The mixed-potential model demonstrated the importance of electrode potential in flotation systems. The mixed potential or rest potential of an electrode provides information to determine the identity of the reactions that take place at the mineral surface and the rates of these processes. One approach is to compare the measured rest potential with equilibrium potential for various processes derived from thermodynamic data. Allison et al. (1971,1972) considered that a necessary condition for the electrochemical formation of dithiolate at the mineral surface is that the measmed mixed potential arising from the reduction of oxygen and the oxidation of this collector at the surface must be anodic to the equilibrium potential for the thio ion/dithiolate couple. They correlated the rest potential of a range of sulphide minerals in different thio-collector solutions with the products extracted from the surface as shown in Table 1.2 and 1.3. It can be seen from these Tables that only those minerals exhibiting rest potential in excess of the thio ion/disulphide couple formed dithiolate as a major reaction product. Those minerals which had a rest potential below this value formed the metal collector compoimds, except covellite on which dixanthogen was formed even though the measured rest potential was below the reversible potential. Allison et al. (1972) attributed the behavior to the decomposition of cupric xanthate. 

Dekker et al. [170] have also shown that the steady state experimental data of the extraction and the observed dynamic behavior of the extraction are in good agreement with the model predictions. This model offers the opportunity to predict the effect of changes, both in the process conditions (effect of residence time and mass transfer coefficient) and in the composition of the aqueous and reverse micellar phase (effect of inactivation rate constant and distribution coefficient) on the extraction efficiency. A shorter residence time in the extractors, in combination with an increase in mass transfer rate, will give improvement in the yield of active enzyme in the second aqueous phase and will further reduce the surfactant loss. They have suggested that the use of centrifugal separators or extractors might be valuable in this respect. 

Pure component physical property data for the five species in our simulation of the HDA process were obtained from Chemical Engineering (1975) (liquid densities, heat capacities, vapor pressures, etc.). Vapor-liquid equilibrium behavior was assumed to be ideal. Much of the flowsheet and equipment design information was extracted from Douglas (1988). We have also determined certain design and control variables (e.g., column feed locations, temperature control trays, overhead receiver and column base liquid holdups.) that are not specified by Douglas. Tables 10.1 to 10.4 contain data for selected process streams. These data come from our TMODS dynamic simulation and not from a commercial steady-state simulation package. The corresponding stream numbers are shown in Fig. 10.1. In our simulation, the stabilizer column is modeled as a component splitter and tank. A heater is used to raise the temperature of the liquid feed stream to the product column. Table 10.5 presents equipment data and Table 10.6 compiles the heat transfer rates within process equipment. 

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