Extraction Process Variables

As a byproduct of the juice concentrate industry, an estimated 500,000 to 1,000,000 tons of wet pulp are produced each crop year. Unlike suggested more exotic sources of dietary fiber, orange pulp is already an established, commonly consumed food component in the American diet. The functional and nutrient properties of washed orange pulp are intimately related to a series of factors. The foremost of these is the orange species but also significant are climatic and crop year variants, harvest maturity, expression and extraction processing variables, uncontrolled enzymatic and microbial activity as well as method of drying. Because of variations in the material, application and development as a fiber has been limited. 

In wet spinning, the solvent extraction rate can be influenced by changing several processing variables including the type and concentration of coagulation fluid, the... 

Complex nutrients, such as yeast extract, are variable in composition and consequently it is difficult to maintain process reproducibility within the narrow window required to produce a product of consistent quality. 

When we analyze the scale-space image of a function (see Section II, B) in order to extract the trends of process variables, we are interested only in a finite number of distinct trends, as they are defined by the interval tree of scale. 

The wavelet decomposition of measured data provides a natural framework for the extraction of temporal features, which characterize operating process variables and their trends. Such characterization, local in fre-... 

Lee, Y.N. and Wiley, R.C., Betalaine yield from a continuous solid-liquid extraction system as influenced by raw product, post-harvest and processing variables, J. Food ScL, 46, 421, 1981. 

A knowledge of the extraction equilibria between the organic and aqueous phases helps to identify the operational variables that can control the solvent extraction process. An example - the extraction of copper from a copper sulfate solution using a chelating reagent (HR) - is considered. This is one of the best studied examples of solvent extraction. Normally, the system would not be described as a water-hydrocarbon dual-phase system, as it is in fact the Cu2+, SO-, H+, R-, and R-, and the equation... 

HPLC methods of determining the amounts of different additives in polymeric materials are preceded by an extraction process or dissolution of the polymer matrix. Although extraction-HPLC is often observed to be superior to the traditional spectroscopic techniques (UV and IR) in analysing additives, it is frequently difficult to obtain reproducible results in view of the variability of the extraction yield. On the other hand, it is equally difficult to obtain quantitative data in the dissolution/reprecipitation-HPLC method because of entrapment of analytes in the polymer precipitate and the potential for high absorption of the additives on the polymer surface. 

The last example differs from the previous examples in this section in that they involved discrete variables, while pressure and temperature are continuous functions. The same problem could also arise in the discrete case. For instance, although the initial design might favor crystallization over extraction, if the sequence of processing steps were changed the extractive process might be preferable. 

From plots of the distribution ratio against the variables of the system— [M], pH, [HA] , [B], etc.—an indication of the species involved in the solvent extraction process can be obtained from a comparison with the extraction curves presented in this chapter see Fig. 4.3. Sometimes this may not be sufficient, and some additional methods are required for identifying the species in solvent extraction. These and a summary of various methods for calculating equilibrium constants from the experimental data, using graphical as well as numerical techniques is discussed in the following sections. Calculation of equilibrium constants from solvent extraction is described in several monographs [60-64]. 

The economics of the solvent extraction process are very dependent upon upstream and downstream portions of the plant. Integration of the total processing step is essential to obtain maximum return. Variables, such as tonnage rates and changes in solution composition, can have a most significant result on the economics of solvent extraction. Generally, economic considerations may be divided into two major areas (1) capital investments and (2) operating costs. 

NN applications, perhaps more important, is process control. Processes that are poorly understood or ill defined can hardly be simulated by empirical methods. The problem of particular importance for this review is the use of NN in chemical engineering to model nonlinear steady-state solvent extraction processes in extraction columns [112] or in batteries of counter-current mixer-settlers [113]. It has been shown on the example of zirconium/ hafnium separation that the knowledge acquired by the network in the learning process may be used for accurate prediction of the response of dependent process variables to a change of the independent variables in the extraction plant. If implemented in the real process, the NN would alert the operator to deviations from the nominal values and would predict the expected value if no corrective action was taken. As a processing time of a trained NN is short, less than a second, the NN can be used as a real-time sensor [113]. 

The variable responses observed are probably the main drawback for the practical use of essential oil as miticides. It must be pointed out that the same plant species often produces essential oils with variable composition because of environmental and/or genetic factors many species have varieties, the so called chemotypes for instance at least seven chemotypes are known for Thymus vulgaris [88,89]. Also the extraction process influences the composition of the essential oils. For these reasons, it is advisable that authors report the composition of the essential oils used in the biological investigations. Unfortunately, only one paper reported this important information [64]. 

The objectives of this work were (1) to evaluate the reliability and performance of this CLLE design in a large-scale scheme for the preparation of samples for biological testing, (2) to compare CLLE recovery to batch LLE recovery for a set of organic probes, (3) to evaluate variability in CLLE performance as a function of sample size, and, above all, (4) to evaluate the effects of background humic materials on the extraction process for both CLLE and batch LLE. 

Summary. It is obvious from the foregoing paragraphs that there is inherent variability in the raw material supply chain before the extraction process itself is even stalled. This will introduce variability into the subsequent process and influence product costs. 

These paragraphs suggest the issues that the extract manufacturer faces in production. Given the many different factors, both in nature and within the extraction process itself, that produce variability, it is perhaps a tribute to the extract manufacturers combination of technology and art built up over a long time that extracts as sold to customers are as consistent as they are. 

Samples of sand spiked with 36 nitroaromatic compounds, 19 haloethers, and 42 organochlorine pesticides, and a standard reference soil (certified for 13 polynuclear aromatic hydrocarbons, dibenzofuran, and pentachlorophenol) were extracted with supercritical carbon dioxide in a two- or four-vessel supercritical fluid extractor to establish the efficiency of the extraction and the degree of agreement of the parallel extraction recoveries. Furthermore, the many variables that influence the extraction process (e.g., flowrate, pressure, temperature, moisture content, cell volume, sample size, extraction time, modifier type, modifier volume, static versus dynamic extraction, volume of solvent in the collection vessel, and the use of glass beads to fill the void volume) were investigated. 

Supercritical fluid extraction system - Hewlett Packard Model 7680A totally automated system with unlimited-capacity reciprocating pump, specially designed extraction chamber with safety interlocks, a variable restrictor nozzle and analyte collection trap. The operation of the extractor is controlled by a personal computer which is a Microsoft Windows-based system. An animated status screen provides real-time monitoring of the extraction process. Table II gives the SFE conditions for the HP extractor. 

Coy, F.B. 2002. Developing computer models for the UREX solvent extraction process and performing a sensitivity analysis of variables used for optimizing flowsheets for actinide transmutation. Thesis. The University of Texas at Austin. 

In the present work a method is described to extract the information necessary for modelling from only a few dynamic experimental runs. The method is based on the measurement of the changes of the temperature and concentration profiles in the reactor under the influence of forced simultaneous sinusoidal variations of the process variables. The characteristic features of the dynamic method are demonstrated using the behaviour of a nonisothermal-nonadiabatic pilot plant fixed bed reactor as an example. The test reaction applied was the hydrogenation of toluene to methylcyclohexane on a commercial nickel catalyst. 

In the molten salt extraction process, the variables that control the values of the americium and plutonium distribution coefficients are temperature, metal composition, salt composition, and total americium. To minimize the variables, the extractions are conducted at a fixed temperature of about 750°C. Slight changes of magnesium content in the metal have a negligible effect upon the value of the americium and plutonium distribution coefficients. The effect of americium concentration... 

Tphis work explores the important variables which must be considered - to design an extractive distillation process. The discussion identifies the economic effects of these variables and their possible interactions. Some of the design variables may have synergistic effects in terms of separation cost while others may not. As a result, the optimum design for an economic extractive distillation process must be a compromise set of values for the different process variables. These compromises are discussed and are illustrated for a particular case—i.e., separation of propane-propylene mixtures. For this commercially important separation fractional distillation is most often used, regardless of the low relative volatility (about 1.13-1.19 at 200 psia). 

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