Composite reliability

In recent decades we have seen an explosion of various spectroscopic techniques for analyzing the elemental composition and chemical states of solid surfaces and films. This explosion has stemmed in part from the large number of surface- or interface-related problems seen in integrated-circuit performance, composite reliability, corrosion, nanostructured components, and so on. Instruments themselves can range from stand-alone units to attachments in national synchrotron facilities or multitechnique systems built around special fabrication sites. However, the basic principle of the technique, and therefore the basic concerns with sample preparation, stay the same. 

A third approach that is commonly used to constrain chemical fluxes compares differently altered materials, such as altered pillow margins and less altered pillow interiors, or samples with or without alteration haloes around veins (e.g., Alt et al., 1986), mineralized and unmineralized zones or differently altered gabbros (e.g., Bach et al., 2001) in order to constrain chemical changes associated with alteration. However, least altered samples only rarely reflect the original composition reliably. A second problem in this approach is the relatively small sample sizes typically analyzed from ocean drilling materials. Typical sample sizes are about 15 cm, which is small when compared with local variability in modal mineralogy. Indeed, individual phenocryst phases can be several millimeters in size. Local variability in modal mineralogy is particularly common in pillow lavas where phenocryst abundances can vary as a function of radial distance from the center or vertically within the center... 

Compound identification (reactant or product) based on chemical analysis must be precise to define composition reliably. Many solids deviate from stoichiometric expectation, there is also the possibility that precursor pro-... 

Industrial concern for quality and process control, as well as in-service examination, has led to an increased demand for composite reliability inspection techniques. New and more sophisticated NDT techniques have been developed to meet this demand. However, there is still the view that the tried and tested conventional methods are generally more acceptable, their limitations understood and appreciated. Despite the development of new NDT techniques for composite examination, conventional NDT techniques will remain favoured to NDT engineers as they are expected to be accepted more readily [1]. The introduction of innovations, in addition to highly proven and accepted reliabilities in flaw detection, is significantly desirable to composite manufacturers and users. 

Assume further that the system probability is given by combining the component reliability states. This probability can be expressed as p = Pc p where is the Kronecker product (Sasty 1999 p. 99). Time derivation of this expression gives further p = Pa PyS + Pa PyS Inserting the component equations in this relation and rearranging using the Kronecker relations gives finally the composite reliability model... 

An electrical grid is assiuned to consist of branches connected in nodes. A branch may consist of generators or power import branches, transmission lines, transformers and load or export branches. In addition contain these main components normally a lot of sub components or factors that can be classified as power transmitting components, protection and reclosing components, human factors and environmental factors. A composite reliability model for each branch is build by model composition taking into account all relevant components and their probability interactions. A typical branch model may have from 1000 to 20.000 composite reliability states. These composite branch models are finally reduced by model aggregation... 

Wang ASD, Pipes RB, Ahmadi A, Thermoelastic expansion of graphite/epoxy unidirectional and angle-ply composites. Composite Reliability ASTM STP580, American Society for Testing and Materials, Philadelphia, 574-585, 1975. 

In addition, according to the standard of convergent validity assessed by FomeU and Larcker (1981), all standardized factor loadings should be greater than 0.5 and should be above 0.6 in terms of composite reliability, as shown in Table 1 that all constructs indicator-factor loadings are above 0.5, all composite reliabilities (CR) are above 0.7, average variance extracted (AVE) is above 0.5. Measurement scales see Appendix A. 

In general, nitrosamines arise only in very low concentrations. Since some of these compounds are a great health hazard, they should be detectable below 0.1 ppm in food for human consumption. The same procedures are available for identifying volatile nitrosamines which have been described earlier for the analysis of aroma constituents (cf. 5.2). However, precautions should be taken during the isolation step. Isolation of nitrosamines should not proceed at low pH since an acid medium in the presence of residual meat nitrites promotes further de novo synthesis of nitrosamines. Since the isolated fraction of neutral volatile confounds, which also includes nitrosamines, is highly conplex in composition, reliable nitrosamines identification by gas chromatographic retention data is not possible. Additional mass spectrometric data are needed to verify the chemical structure. 

Oliverira, A. M., A. C. G. Melo, and L. M. V. G. Pinto. Consideration of Equipment Failure Parameter Uncertainties in Bus Composite Reliability Indices. Proceedings of the IEEE Power Engineering Society Winter Meeting, 1999,448-453. 

The typical approach to reliability assessment is the Cronbach s a coefficient. However, Cronbach s a is based on the restricted assumption of equal importance of all indicators. Following Hair et al. (1995), the composite reliability (pc) and the average variance extracted (AVE) of multiple indicators of a constmct can be used to assess reliability of a constmct. The formulas for calculating them are shown below. When AVE is greater than 0.50 and is greater than 0.70, it implies that the variance by the trait is more than that by error components (Hair et al. 1995). 

CFI = 1.00, NNFI = 1.00). All the factor loadings are greater than 0.80 and significant at p < 0.01 based on t-values. This indicates good convergent validity. The estimate of AVE of 0.75 and the composite reliability of 0.92 exceed the critical value of 0.50 and 0.70 respectively, providing evidence of good reliability. 

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