Research errors

The measuring error of crack depth by means of electropotential devices is considered to be approximately 10%[2]. The research work performed gives us an opportunity to maintain it that is practice such a measuring error can be higher in many times et some probably combinations of parameters h, I, T. 

The essential assumption of this manuscript is the existence of a constant variance of Gaussian errors along the trajectory. While we attempted to correlate the variance with the high frequency motions, many uncertainties and questions remain. These are topics for future research. 

There is a fundamental difference between such scientific controversies and what simply can be called scientific fraud, i.e., deliberate falsification or fudging of data. Sloppy experimental work or data keeping can also lead to questionable or incorrect conclusions, and, although these violate established scientific standards and must be corrected (as they will), they do not necessarily represent deliberate fraud. In all this, the professor has a strict personal responsibility. As he/she is getting most of the recognition for the accomplishment of the research, it is only natural that he/she must also shoulder the responsibility for any mistakes, errors, or even falsifications. It is not accepta-... 

The system of atomic units was developed to simplify mathematical equations by setting many fundamental constants equal to 1. This is a means for theorists to save on pencil lead and thus possible errors. It also reduces the amount of computer time necessary to perform chemical computations, which can be considerable. The third advantage is that any changes in the measured values of physical constants do not affect the theoretical results. Some theorists work entirely in atomic units, but many researchers convert the theoretical results into more familiar unit systems. Table 2.1 gives some conversion factors for atomic units. 

Researchers must be particularly cautious when using one estimated property as the input for another estimation technique. This is because possible error can increase significantly when two approximate techniques are combined. Unfortunately, there are some cases in which this is the only available method for computing a property. In this case, researchers are advised to work out the error propagation to determine an estimated error in the final answer. 

There are numerous articles and references on computational research studies. If none exist for the task at hand, the researcher may have to guess which method to use based on its assumptions. It is then prudent to perform a short study to verify the method s accuracy before applying it to an unknown. When an expert predicts an error or best method without the benefit of prior related research, he or she should have a fair amount of knowledge about available options A savvy researcher must know the merits and drawbacks of various methods and software packages in order to make an informed choice. The bibliography at the end of this chapter lists sources for reviewing accuracy data. Appendix A of this book provides short reviews of many software packages. 

Try quasi-Newton calculations starting from structures that look like what you expect the transition structure to be and that have no symmetry. This is a skill that improves as you become more familiar with the mechanisms involved, but requires some trial-and-error work even for the most experienced researchers. 

Once you are experienced at finding transition structures for a particular class of reactions, you will probably go directly to the technique that has been most reliable for those reactions. Until that time, the checklist above is our best advice for finding a transition structure with the least amount of work for the researcher and the computer. Regardless of experience, it is common to experience quite a bit of trial and error in finding transition structures. Even experienced researchers find that the way they have been regarding a reaction is often much more simplistic than the molecular motions actually involved. 

The control chart is set up to answer the question of whether the data are in statistical control, that is, whether the data may be retarded as random samples from a single population of data. Because of this feature of testing for randomness, the control chart may be useful in searching out systematic sources of error in laboratory research data as well as in evaluating plant-production or control-analysis data. ... 

Nonetheless, these methods only estimate organ-averaged radiation dose. Any process which results in high concentrations of radioactivity in organs outside the MIRD tables or in very small volumes within an organ can result in significant error. In addition, the kinetic behavior of materials in the body can have a dramatic effect on radiation dose and models of material transport are constandy refined. Thus radiation dosimetry remains an area of significant research activity. 

Valid emission factors for each source of pollution are the key to the emission inventory. It is not uncommon to find emission factors differing by 50%, depending on the researcher, variables at the time of emission measurement, etc. Since it is possible to reduce the estimating errors in the... 

Revenues. The selling price for the major product and the quantity to be sold each year must be estimated. If the product is new, this can be a major study. In any case, input is needed from sales, transportation, research, and any other department or individual who can increase the accuracy of the revenue data. The operating costs may be off by 20% without fatal results, but a 20% error in the sales volume or price w ill have a much larger impact. Further, the operating costs are mostly within the control of the operator, while the sales price and volume can be... 

The mathematical principles of convective heat transfer are complex and outside the scope of this section. The problems are often so complicated that theoretical handling is difficult, and full use is made of empirical correlation formulas. These formulas often use different variables depending on the research methods. Inaccuracy in defining material characteristics, experimental errors, and geometric deviations produce noticeable deviations between correlation formulas and practice. Near the validity boundaries of the equations, or in certain unfavorable cases, the errors can be excessive. 

Because most research effort in the human reliability domain has focused on the quantification of error probabilities, a large number of techniques exist. However, a relatively small number of these techniques have actually been applied in practical risk assessments, and even fewer have been used in the CPI. For this reason, in this section only three techniques will be described in detail. More extensive reviews are available from other sources (e.g., Kirwan et al., 1988 Kirwan, 1990 Meister, 1984). Following a brief description of each technique, a case study will be provided to illustrate the application of the technique in practice. As emphasized in the early part of this chapter, quantification has to be preceded by a rigorous qualitative analysis in order to ensure that all errors with significant consequences are identified. If the qualitative analysis is incomplete, then quanhfication will be inaccurate. It is also important to be aware of the limitations of the accuracy of the data generally available... 

Norros, L., Samatti, P. (1986). Nuclear Power Plant Operator Errors during Simulator Training. Research reports 446, Technical Research Centre of Finland. 

Pennycook, W. A., Embrey, D. E. (1993). An Operating Approach to Error Analysis. In Proceedings of the First Biennial Canadian Conference on Process Safety and Loss Management. Edmonton, 24th April. Waterloo, Ontario, Canada Institute for Risk Research, University of Waterloo. 

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