Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Errors experience

At low pressures, it is often permissible to neglect nonidealities of the vapor phase. If these nonidealities are not negligible, they can have the effect of introducing a nonrandom trend into the plotted residuals similar to that introduced by systematic error. Experience here has shown that application of vapor-phase corrections for nonidealities gives a better representation of the data by the model, oven when these corrections... [Pg.106]

Whether the optimum phase system is arrived at by a computer system, or by trial and error experiments (which are often carried out, even after computer optimization), the basic chromatographic data needed in column design will be... [Pg.364]

Fitts, P. M., Jones, R. E. (1947). Analysis of Factors Contributing to 460 "Pilot Error" Experiences in Operating Aircraft Controls. Reprinted in H. W. Sinaiko (Ed.) (1961), Selected Papers on Human Factors in the Design and Use of Control Systems. New York Dover. [Pg.369]

Oxidation of the A-ring lactam is dearly the key step in the finasteride process. Although this reaction could have been optimized through trial and error, experiments designed to provide insight into the mechanism gave us the understanding needed to identify the best conditions most effidently. [Pg.105]

The summary of our many try-n-error experiments suggests that for realization of concept proposed by Figure 2, it is necessary to enable the following conditions ... [Pg.314]

A departure from traditional approaches of depositing a significant amount of metal onto carbon precursor differentiated our experiments from the state of the art literature. Through several trial and error experiments, it was possible to formulate several key principles, which should constitute a design of the metal/carbon composites. Among those are ... [Pg.338]

Whether the optimum phase system is arrived at by a computer system, or by trial and error experiments (which are often carried out, even after computer optimization), the basic chromatographic data needed in column design will be identified. The phase system will define the separation ratio of the critical pair, the capacity ratio of the first eluted peak of the critical pair and the capacity ratio of the last eluted peak. It will also define the viscosity of the mobile phase and the diffusivity of the solute in the mobile phase. [Pg.181]

One of the major problems is that pharmaceutical formulations are complex systems and that they are often developed empirically under a high time pressure on the basis of trial and error experiments. This procedure can easily lead to a nonrobust formulation. [Pg.569]

Thus, concerning drug load, only the tablet formulation is shown to be robust. Therefore, in the case of poorly wettable drug, the effect of dose can have direct impact on the decision whether to develop a tablet or a capsule dosage form. Such effects are not uncommon in Trial and Error experiments. Owing to lack of scientiLcally based formulation work, it is often impossible to understand the reasons for the behavior of the capsule versus the tablet formulation. [Pg.571]

Since the discovery of the Loeb-Sourirajan technique in the 1960s, development of the technology has proceeded on two fronts. Industrial users of the technology have generally taken an empirical approach, making improvements in the technique based on trial and error experience. Concurrently, theories of membrane formation based on fundamental studies of the precipitation process have been developed. These theories originated with the early industrial developers of membranes at Amicon [19,22,24] and were then taken up at a number of academic centers. Unfortunately, much of the recent academic work is so complex that many industrial producers of phase separation membranes no longer follow this literature. [Pg.101]

Goodyear was determined to solve the problems inherent in natural rubber. With no formal training in chemistry, his work was based on trial and error, experimenting with different methods of processing and additives such as magnesia. The solution he discovered resulted partly from serendipity and partly from constant work. [Pg.177]

Many trial-and-error experiments can be avoided during the development of a displacement chromatographic separation, when the isotherm of at least the most strongly adsorbed sample component is known. Therefore, as the next step, the adsorption isotherms of the most retained iscmers of chloroaniline and Ibuprofen, the examples discussed above, were determined as shown in Figs. 8 and 9. It can be seen by cxnparing the isotherms of the solute and prospective displacer pairs that indeed p-nitrophenol can be used as a displacer for the separation of the chloroaniline iscmers. The situation is more complicated with Ibuprofen and 4-t-butylcyclchexanol because their isotherms cross each other at 1.5 irM. This indicates that successful separations can be expected only below this concentration level. Other examples of crossing isotherms were also reported (69). [Pg.191]

Starting up a jacketed batch reactor requires control of the heat-up and cool-down rates. To do this, the jacket heat-transfer-fluid temperatures have to be determined and set. This can be done by trial-and-error experiments, but it is often quicker and more straightforward to simply make a trial heat-up and then plug the results into time-dependent heat-transfer equations. Here s how to do this for steam or hot-water jacketed reactors. [Pg.57]

It could be argued that drug discovery strategies of the past were analogous to fishing with a line and hook. A systematic series of trial and error experiments such as quantitative structure-activity relationship (QSAR) methodologies, for example, were commonplace. The process was iterative and labor intensive. A chemist or biologist had relatively few restrictions, particularly with time, to explore ideas and test hypotheses. The overall endeavor was more craft than process. [Pg.559]

The first two approaches using definitive or primary or reference methods within one single laboratory require that in this laboratory everything is done to eliminate sources of systematic errors. Experience has demonstrated that it is very difficult to achieve 100% certainty and that within the laboratory a systematic bias does not remain. An additional confirmation through an — even limited — interlaboratory study is therefore advisable. Such an approach is used by NIST the single laboratory certification complies with the demand of US law that results and certificates must be NIST traceable . [Pg.172]

At the planning of appraisal of the sensor s error experiments, the test officer usually knows the list of the influencing factors and their boundary conditions. From the theory of experiment point of view, the optimal test setup would be the multifactor experiment at which both all influencing factors and measuring gas concentrations would be varied within all ranges with following appraisal of the dispersion of the output signal. However, it is impossible to implement the optimal test setup in practice. [Pg.265]

It would be extremely difficult to predict by calculation what sequence of joystick movements would be needed to produce a desired X-T trajectory, and in feet impossible unless all the details of the reaction were known ahead of time. However, a human operator could quickly develop considerable intuitive expertise through repeated trial-and-error experience with a simulator or with a real reactor. This would raise the role of the technician in charge from the traditional reactor operator to a reaction phase plane pilot whose skill in covering the desired area of the reaction phase plane would be a great asset to expediting experimental work. [Pg.121]


See other pages where Errors experience is mentioned: [Pg.105]    [Pg.328]    [Pg.761]    [Pg.476]    [Pg.469]    [Pg.282]    [Pg.84]    [Pg.350]    [Pg.13]    [Pg.490]    [Pg.100]    [Pg.361]    [Pg.312]    [Pg.188]    [Pg.135]    [Pg.316]    [Pg.202]    [Pg.73]    [Pg.1018]    [Pg.177]    [Pg.1364]    [Pg.4]    [Pg.7]    [Pg.84]    [Pg.366]    [Pg.73]    [Pg.381]    [Pg.388]   
See also in sourсe #XX -- [ Pg.7 , Pg.194 ]




SEARCH



Error Analysis of Experiments

Errors in Response Experiments

Experiment error

Experiment error

Experiment-wise error rate

Normal error curve experiment

Selective pulse experiments, systematic errors

Sources of Error in High-Throughput Biological Experiments

© 2024 chempedia.info