Quantitative Consequence Evaluation

Quantitative consequence evaluation requires determination of the blast overpressure and other explosion or fire effects that can impact a process plant building and a detailed analysis of the building s response. 

If the slopes of the absorption/time curves differ considerably, a positive hit is indicated (i.e., an enantioselective lipase-variant has been identified) (16). Figure 5 shows two typical experimental plots, illustrating the presence of a non-selective lipase (top) and a hit (bottom) (16). As a consequence of the crudeness of the test, quantitative evaluation is not possible. Therefore, the hits need to be investigated separately in laboratory-scale reactions and evaluated quantitatively by conventional chiral GC. About 800 plots of this kind can easily be recorded per day. A total of 40 000 lipase-variants were generated by epPCR, saturation mutagenesis, cassette mutagenesis, and DNA shuffling and screened in the model reaction. 

HAZAN, on the other hand, is a process to assess the probability of occurrence of such accidents and to evaluate quantitatively the consequences of such happenings, together with value judgments, in order to decide the level of acceptable risk. HAZAN is also sometimes referred to as Probabilistic Risk Assessment (PRA) and its study uses the well-established techniques of Fault Tree Analysis and/or Event Tree Analysis ... 

The simplest analytical information that can be obtained with the aid of FFF is the homogeneity of the sample or evidence for the presence of a compound of interest in the fractionated sample by the appearance of a peak in the expected interval of retention volume. In some cases, comparison of the retention volume and the peak shape of the investigated component with the peak shape of a reference sample can provide sufficient qualitative analytical information on sample purity and homogeneity. The peak areas in the fractogram can be used to evaluate quantitatively concentrations of the detected components provided that the relationship between detector response and concentration or quantity of the detected component is known. This relationship is usually determined by a calibration procedure. However some sample is lost in the void peak so that it is not possible to relate the detected concentration to that of the original sample consequently, concentration determinations can more advantageously serve to compare the relative concentrations of the fractionated components. 

SUMMARY OF FINDINGS. The PSM Rule requires a qualitative evaluation of the consequences of engineering and/or administrative control failures, to show the range of possible safety and health effects on workers and offsite populations. This information can be obtained from the PrHA by selecting those scenarios that cover the range of possible health effects, and then discussing the existing protection (see Section 3.2). It may be necessary to conduct a rudimentary, quantitative consequence evaluation in order to provide the qualitative information required. 

Consequently, it is necessary to check the definition of a rate constant very carefully when evaluating quantitative data. 

Another major step forward for radio-TLC came in the early 1980s when the so-called linear analyzer was introduced. This instrument was easier to use and more sensitive than the old scanners and was automated to the extent that up to four plates could be run overnight. More details are given below. As a consequence, improved quantitative results were obtained and analysis time was shortened. However, resolution was still not as good as that obtained by using autoradiography, and two-dimensional plates could not be easily evaluated. 

Consequently, volumes of the basal ganglia in brain were reconstructed from 2D SWI and 3D MP-RAGE and were compared to verify influence of the iron deposition. Also, each ROI was visualized using different colors in Fig 2 to evaluate quantitative volume. We suggest that volumetry technique using SWI or TIWI can provide quantitative and visual data by measuring the volume of interest (VOI) pattern for the patients with disease related to iron deposition. To optimize the results, we will devise the objective ROI model for volumety through various SWI sequences in future study. 

It should be borne in mind that optimizing the expectation of a performance metric (e.g., NPV) has proven to be incompatible with lowering risk measures. The maximization of expected metrics by itself is not an appropriate objective since solutions with higher risk exposure are obtained (Barbaro and Bagajewicz 2004). Consequently, a quantitative evaluation of risk is desirable in stochastic models in order to manage such a riade-off. A comprehensive discussion of risk concepts and measures is presented in Bagajewicz (2005). 

Whereas no quantitative consequence analysis is required by this legislation, the process ha2ards analysis must include a quaHtative evaluation of the possible effects of failure of controls on employees. Details concerning development and implementation of programs for these subjects are available (37-39). 

Process Hazards Analysis. Analysis of processes for unrecogni2ed or inadequately controUed ha2ards (see Hazard analysis and risk assessment) is required by OSHA (36). The principal methods of analysis, in an approximate ascending order of intensity, are what-if checklist failure modes and effects ha2ard and operabiHty (HAZOP) and fault-tree analysis. Other complementary methods include human error prediction and cost/benefit analysis. The HAZOP method is the most popular as of 1995 because it can be used to identify ha2ards, pinpoint their causes and consequences, and disclose the need for protective systems. Fault-tree analysis is the method to be used if a quantitative evaluation of operational safety is needed to justify the implementation of process improvements. 

The acronym for chemical process quantitative risk analysis. It is the process of hazard identification followed by numerical evaluation of incident consequences and frequencies, and their combination into an overall measure of risk when applied to the chemical process industry. It is particularly applied to episodic events. It differs from, but is related to, a probabilistic risk analysis (PRA), a quantitative tool used in the nuclear industry... 

The development of a quantitative estimate of risk based on engineering evaluation and mathematical techniques for combining estimates of incident consequences and frequencies... 

The main output from this stage is a detailed assessment of the human error problem areas. If possible this should include quantitative data on the incidence of errors and the significance of their consequences. This will provide a valuable baseline against which to evaluate the success of the error management program. 

Chemical Process Quantitative Risk Analysis(CPQRA) The numerical evaluation of both incident consequences and probabilities or frequencies and their combination into an overall measure of risk. 

In a more quantitative sense, cause-consequence analysis may be viewed as a blend of fault tree end event tree analysis (discussed in tlie two preceding cliapters) for evaluating potential accidents. A major strengtli of cause-consequence analysis is its use as a communication tool. For example, a cause-consequence diagram displays the interrelationships between tlie accident outcomes (consequences) and Uieir basic causes. The method can be used to quantify the expected frequency of occurrence of the consequences if the appropriate chita are available. 

Comparison of Eq. (184) with Eq. (183) shows the effect of size distribution for the case of fast chemical reaction with simultaneous diffusion. This serves to emphasize the error that may arise when one applies uniform-drop-size assumptions to drop populations. Quantitatively the error is small, because 1 — is small in comparison with the second term in the brackets [i.e., kL (kD)112). Consequently, Eq. (184) and Eq. (183) actually give about the same result. In general, the total average mass-transfer rate in the disperser has been evaluated in this model as a function of the following parameters ... 

The Cl 8 reverse phase exhibits the maximum dispersive interactions with the solutes and is thus, chosen when the difference in dispersive character of the solutes is small or subtle. Employing a Cl 8 reverse phase accentuates the dispersive interactions with the solutes and consequently improves their relative retention. Cl 8 columns also exhibit a somewhat higher loading capacity and so large charges can be placed on the column before overload occurs. This can be useful in trace analysis, where large charges are often necessary to detect the minor components at a level where they can quantitatively evaluated. 

Mechanistic Approaches. Adequate and appropriate river-quality assessment must provide predictive information on the possible consequences of water and land development. This requires an understanding of the relevant cause and effect relationships and suitable data to develop predictive models for basin management. This understanding may be achieved through qualitative, semi-quantitative or quantitative approaches. When quantitative or semi-quantitative methods are not available the qualitative approach must be applied. Qualitative assessments involve knowledge of how basin activities may affect river quality. This requires the use of various descriptive methods. An example of this kind of assessment is laboratory evaluation of the extent to which increases in plant nutrients, temperature or flow may lead to accelerated eutrophication with consequent reduction of water quality. 

The different location of polar and amphiphilic molecules within water-containing reversed micelles is depicted in Figure 6. Polar solutes, by increasing the micellar core matter of spherical micelles, induce an increase in the micellar radius, while amphiphilic molecules, being preferentially solubihzed in the water/surfactant interface and consequently increasing the interfacial surface, lead to a decrease in the miceUar radius [49,136,137], These effects can easily be embodied in Eqs. (3) and (4), aUowing a quantitative evaluation of the mean micellar radius and number density of reversed miceUes in the presence of polar and amphiphilic solubilizates. Moreover it must be pointed out that, as a function of the specific distribution law of the solubihzate molecules and on a time scale shorter than that of the material exchange process, the system appears polydisperse and composed of empty and differently occupied reversed miceUes [136],... 

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