Performance Measure - Minimum Time

Mujtaba and Macchietto (1998) chose the minimum time as the most suitable performance measure, because the separation requirements (e.g. product purities) are fixed and quantitative measure, q could be easily used. 

The effects of column holdup can be easily correlated in terms of q and of the minimum batch time required to achieve a given separation task. 

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There is a bewildering variety of multidimensional NMR techniques available to the modem NMR spectroscopist interested in stmcture elucidation, and used in a concerted fashion these provide efficient and economical tools for determining chemical structures. There is a trade-off implicit in the use of multidimensional experiments, between the volume of information that they provide and the minimum time taken to perform them in most cases the extended experimental duration is more than compensated for by the wealth of structural information revealed. For a small proportion of stmctural problems, however, such experiments may provide far more information than is actually required, and where only a few critical parameters need to be measured they may represent a far from efficient use of spectrometer time. 

For an adequate performance of the PIMMS it is necessary to install appropriate pressures and gas flows in the system, as well as a minimum time delay for the sample to reach the ionization chamber. The flow time of the sample gas governs the temporal resolution of the PIMMS measurements. Since the pressure of the plasma and sample gases are usually much higher at their origin than allowed in the plasma and the ionization chamber, respectively, there is a need for pressure reduction which will inevitably introduce a time delay. 

The performance criteria of a batch distillation column can be measured in terms of maximum profit, maximum product or minimum time (Mujtaba, 1999). In distillation, whether batch, continuous or extractive, purity of the main products must be specified as it is driven by the customer demand and product prices. The amount of product and the operation time can be dictated by economics (maximum profit) or one of them can be fixed and the other is obtained (minimum time with fixed amount of product or maximum distillate with fixed operation time). The calculation of each of these will require formulation and solution of optimisation problems. A brief description of these optimisation problems is presented below. Further details will be provided in Chapter 5. 

Reduction in hatch time For a given fresh feed and a given separation, the column performance is measured in terms of minimum batch time required to achieve a desired separation (specified top product purity (x D]) and bottom product purity (x B2) for binary mixture). Then an optimal amount and composition of recycle, subject to physical bounds (maximum reboiler capacity, maximum allowable purity of the off-cut) are obtained in an overall minimum time to produce the same separation (identical top and bottom products as in the... 

Mujtaba (1997) used the maximum distillate problem to compare the performances of the two types of distillation columns (CBD and continuous). With the amount of initial charge and the feed flow rate fixed in a continuous column, the operation time (pass time) also becomes fixed. The performance measure using maximum distillate problem allows fixing of the operation time. Other types of optimisation problems such as minimum time or maximum profit problems (presented in the previous chapters) are not suitable for the purpose of comparing the performances of... 

Mujtaba (1997) used the minimum time to evaluate the performance of continuous column operation under multiple separation duties. However, time does not explicitly appear in continuous column model equations but the feed rate is a measure of the batch time (t = BJF). Note, maximisation of the feed rate will therefore ensure minimisation of the batch time. 

Minimum time is chosen as the measure to compare the performances of IBD and CBD columns. Minimum time optimisation problem similar to that presented in section 5.2.1 is considered where reflux ratio (r) is optimised for a CBD column and... 

With many repetitive steps, the HX-MS experiment is ideally suited to automation. Protein manipulations, dilution with D O, timing, exchange quench events, and HPLC are aU amenable to automation. In a typical differential HX experiment, two protein states are compared the control sample A and comparator sample B. In order to profile the HX kinetics of each protein state, it is common to measure the HX versus time profile across a numba" of time points, plus separate controls for no D O (H O buffer) and a maximum exchange control (generated by an extended exchange event with a reduced and denatured protein sample) (see Figure 12.3a). For each of these HX time points, it is prudent to perform a minimum of three replicate experiments to allow for statistical comparison between the two protein conditions. It is therefore common for a single differential HX-MS dataset to be comprised of in excess of 40 individual incubation and LC-MS experiments. 

This view is quite at variance with the direct interconversion between I and II proposed on the basis of NMR studies [41]. These different views correspond to measurements performed at different time scales. NMR and QENS measure only probabilities averaged over rather long time scales, compared to the transfer rate of a single proton. Only vibrational spectroscopy can probe the quantum regime and distinguish intermediate configurations. Similar double minimum potentials have... 

The operability measure is based on the idea that the time spent away from the desired set point is linked to potential losses due to off-specification products and economic penalties for non-optimal performance. Different types of feedback controllers can be utilized to evaluate this operability measure. However, a performance measure independent of the feedback controller to be used and capable of assessing the inherent limitations of the process is desirable. The minimum-time optimal controller suits these demands very well. The approach is based on an implied assumption that a feedback controller exists that will deliver a closed-loop dynamic operability close to the one calculated here by use of the optimal open-loop controller. For similar reasons, Carvallo [63] employed the minimum time optimal controller to calculate the time it would take the process to respond to the worst disturbance and/or set-point change. 

Decision 2002/657/EC introduces criteria for confirmatory analysis, based on the so called identification points (IPs). Then, for confirmation of Group A substances, a minimum of four IPs are required, whereas for compounds listed in Group B the minimum number of IPs is set to three for a satisfactory confirmation of a compounds identity. Although the cited document still accepts detection techniques like diode-array (DAD) and fluorimetric detection (ELD) as possible confirmatory techniques, the confirmation of veterinary residues in food is performed nowadays by LC coupled to different MS detection systems. The system of IPs relies on the identification power of the different mass analyzers. For instance, a low resolution mass spectrometer (e.g., triple quadru-pole, QqQ or ion trap IT), provides 1.0 IP for the precursor ion and 1.5 IPs for each product ion. By contrast, high resolution mass spectrometers (HRMS resolution >20,000 fwhm, full width at half maximum) provide 2.0 IPs for the precursor ion and 2.5 IPs for each product ion, which means that (2 + 2.5n) IPs can be acquired when working in the product ion scan mode. In addition to IPs, the retention time of the suspected peak has to correspond to the measured retention time of the relative standard, and the area ratio between the selected ion traces has to be equal in the sample and in the standard [12]. 

A more realistic way of calculating analyte DL performance in your sample matrices is to use method detection limit (MDL). The MDL is broadly defined as the minimum concentration of analyte that can be determined from zero with 99% confidence. MDLs are calculated in a similar manner to IDLs, except that the test solution is taken through the entire sample preparation procedure before the analyte concentration is measured multiple times. This difference between MDL and IDL is exemplified in EPA Method 200.8, where a sample solution at 2-5 times the estimated IDL is taken through all the preparation steps and analyzed. The MDL is then calculated in the following manner ... 

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