Computational research analytical methods

The use of computers is essential in probabilistic design (Siddal, 1983). However, research has shown that even the most complete computer supported analytical methods do not enable the designer to predict reliability with sufficiently low statistical risk (Fajdiga et al., 1996). Far more than try to decrease the statistical risk, which is probably impossible, it is hoped that the approach will make it possible to model a particular situation more completely, and from this provide the necessary redesign information which will generate a reliable design solution. 

Catalyst testing and evaluation have been revolutionized by computers, automated test reactors, and analytical methods. With modem equipment, researchers can systematically prepare and screen many catalysts in a short time and efftciendy deterrnine, not only the initial catalytic activity and selectivity, but also the stabiUty and the appearance of trace products that may indicate some new catalytic properties worthy of further development. 

Revolutions are taking place in the way in which research is done - in computation, in bioinformatics, in analytical methods, and in information management. Stanford s High Wire Press (http //highwire.stanford.edu), for example, lets the individual researcher explore the most recent discoveries on line via topic maps or citation trails. How can our researchers take full advantage of these revolutions ... 

The electrochemical aspects of corrosion research have been the subject of some computer-controlled instrumentation [11]. It seems likely, in this case, that electrochemistry alone is not the answer and other techniques, such as spectroscopy and analytical methods, need to supplement the electrochemical measurements. 

Medicine and Pharmaceuticals. Applied mathematics, particularly the use of Fourier analysis and wavelet theory, has sparked explosive growth in the fields of medicine and pharmaceutical development. The enhanced analytical methods available to chemists and bioresearchers through NMR and Fourier transform infrared (FTIR) spectroscopy feciUtate the identification and investigation of new compounds that have potential pharmaceutical applications. In addition, advanced statistical methods, computer modeling, and epidemiological studies provide the foundation for unprecedented levels of research. 

Nevertheless, the claim that we have entered an age of computer-based analytical chemistry (COBAC) is inappropriate and overly optimistic computer-aided" analysis would be a more satisfactory description, and one more consistent with terminology adopted in other disciplines. Artificial intelligence." so-called expert systems [22], neural networks, and genetic algorithms will undoubtedly be increasingly important in the analytical chemistry of the future, but in most cases probably in the context of relatively complex routine investigations supported by extensive previous experience. It is unlikely that such methods will prove optimal even in the long term with respect to analytical research in uncharted waters, especially if results are required near the limit of detectability. 

The problems of response variability and reliability of structures with stochastic properties under dynamic loading are currently the subject of extensive research in the fields of computational stochastic dynamics and earthquake engineering. Both problems deal with the computation of the statistical characteristics of the response and have important practical applications, such as the estimation of seismic fragility curves which are used to assess the vulnerability of structures due to earthquakes. As the existing analytical methods for the evaluation of structural response variability and reliability can only be used in few special cases, this chapter is mainly focused on approximate methods and simulation. A numerical example involving a steel frame is also provided to illustrate the presented theoretical concepts. 

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