Recovery variable

Little et al. (30) found that the recovery efficiency of both IAA and ABA could vary up to fivefold. We have demonstrated the same type of variability (Table 2). Examination of the data from Little et al. (30) as well as from my research group (Table 2) shows that recovery variability for ABA is not as great as for IAA. Thus when analyzing for both compounds from the same sample, one needs to use two internal standards. 

Reprinted from Hartwick et at. (HIO) by courtesy of Marcel Dekker, Inc., New York. Recovery variable, pH dependent. 

Fig. 2.4. An excitable FHN system subjected to an external driving Sy t) acting on the slow recovery variable y (left) or (t) acting on the voltage variable x (right) as described by eq. (2.11). The signal applied to y moves the y-nullcline upwards and downwards, thus moving the stable fixed point towards the excitation barrier and back again. The signal applied to x moves the aj-nullcline upwards and downwards, thus having a similar effect on the the excitation barrier.

Panfilov and Rudenko [34] published results of numerical experiments using Pushchino kinetics, with Dj = 0, that lend credence to equations (21). (By convention, when Di D2, Dy refers to the excitation variable and D2 to the recovery variable.) They found R< N and R( B to be linear functions of K even up to very high curvatures, 0 < k < 3/Aq (where Aq is the wavelength of the underlying spiral wave). They also found that scroll rings may expand (62 < 0) as well as shrink (62 > 0) when diffusion coefficients are not equal. 

For example in estimating the ultimate recovery (UR) for an oil reservoir, one would need to use the following variables ... 

From the probability distributions for each of the variables on the right hand side, the values of K, p, o can be calculated. Assuming that the variables are independent, they can now be combined using the above rules to calculate K, p, o for ultimate recovery. Assuming the distribution for UR is Log-Normal, the value of UR for any confidence level can be calculated. This whole process can be performed on paper, or quickly written on a spreadsheet. The results are often within 10% of those generated by Monte Carlo simulation. 

An important application of foams arises in foam displacement, another means to aid enhanced oil recovery. The effectiveness of various foams in displacing oil from porous media has been studied by Shah and co-workers [237, 238]. The displacement efficiency depends on numerous physicochemical variables such as surfactant chain length and temperature with the surface properties of the foaming solution being an important determinant of performance. 

The spht is of variable thickness, and some of the spUt is too thin for leather production. The thin parts are trimmed off and discarded for coUagen recovery. The trimmed spUt is tanned separately. 

Gas purification processes fall into three categories the removal of gaseous impurities, the removal of particulate impurities, and ultrafine cleaning. The extra expense of the last process is only justified by the nature of the subsequent operations or the need to produce a pure gas stream. Because there are many variables in gas treating, several factors must be considered (/) the types and concentrations of contaminants in the gas (2) the degree of contaminant removal desired (J) the selectivity of acid gas removal required (4) the temperature, pressure, volume, and composition of the gas to be processed (5) the carbon dioxide-to-hydrogen sulfide ratio in the gas and (6) the desirabiUty of sulfur recovery on account of process economics or environmental issues. 

Other energy considerations for cooling towers include the use of two-speed or variable-speed drives on cooling-tower fans, and proper cooling-water chemistry to prevent fouling in users (see Water, industrial water treatment). Air coolers can be a cost-effective alternative to cooling towers at 50—90°C, just below the level where heat recovery is economical. 

Factors affecting RO membrane separations and water flux include feed variables such as solute concentration, temperature, pH, and pretreatment requirements membrane variables such as polymer type, module geometry, and module arrangement and process variables such as feed flow rate, operating time and pressure, and water recovery. 

In addition to variable chemical stabiUty the carbapenems are susceptible to P-lactam cleavage by a dehydropeptidase en2yme (DHP-I) located on the bmsh borders of the kidney (53). Clinically, MK 0787 (18) is used with an inhibitor of this en2yme, cil a sta tin [78852-98-9] (MK 0791) (34), 16 26 2 5 dramatic effect not only on the urinary recovery of the drug, but also reduces any nephrotoxic potential (52) (see Enzyme... 

Finding the best solution when a large number of variables are involved is a fundamental engineering activity. The optimal solution is with respect to some critical resource, most often the cost (or profit) measured in doUars. For some problems, the optimum may be defined as, eg, minimum solvent recovery. The calculated variable that is maximized or minimized is called the objective or the objective function. 

Optimization. Optimi2ation of the design variables is an important yet often neglected step in the design of extractive distillation sequences. The cost of the solvent recovery (qv) step affects the optimi2ation and thus must also be included. Optimi2ation not only yields the most efficient extractive distillation design, it is also a prerequisite for vaUd comparisons with other separation sequences and methods. 

Extensive design and optimization studies have been carried out for this sequence (108). The principal optimization variables, ie, the design variables that have the largest impact on the economics of the process, are the redux ratio in the azeo-column the position of the tie-line for the mixture in the decanter, determined by the temperature and overall composition of the mixture in the decanter the position of the decanter composition on the decanter tie-line (see Reference 104 for a discussion of the importance of these variables) and the distillate composition from the entrainer recovery column. 

Sample stability becomes increasingly important as the time between sampling and analysis increases. Effects of temperature, trace contaminants, and chemical reactions can cause the collected species to be lost from the collection medium or to undergo a transformation that will prevent its recovery. Nearly 100% recovery is also required because a variable recovery rate will prevent quantification of the analysis. Interference should be minimal and, if present, well understood. 

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