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In this paper, first the definitions of variability and ergodicity are discussed. This is followed by an overview of variography, and the importance of sequential stochastic simulation is emphasized. The main uncertainties of variograms are discussed, followed by the methods for decreasing this uncertainty. It is stressed that additional geologic information can be obtained from variograms, even beyond the ranges of influence. Possibilities of local evaluation of the gh values and ranges of influence are presented. The main idea of the paper is that the gh values and the ranges of influence are continuous random variables. Up to now variograms were evaluated mainly for geomathematical purposes and their direct geologic evaluation was neglected. The author presents examples of such kinds of evaluation.

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The paper deals with the approaches to the response analysis of large transport and lifeline structures. The background theory for simplified analysis is presented. Seismic inputs represent the cases of explosion impacts and large near field earthquake effects. 3DOF and 6DOF input models are based on surface wave theory and applied for calculations and shaking table experiments. Examples of seismic motion simulations are those obtained during large MASTER shaking table tests in Enel.Hydro-ISMES Seriate, Italy in the framework of EC international projects.

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Abstract

Compound-specific isotope analysis (CSIA) is fast becoming an important tool to provide chemical evidence in a forensic investigation. Attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large dataset is analyzed and the isotopic differences between samples are subtle. Thus, this study intends to demonstrate any linkages between diesel fuels in a large number of datasets where subtlety in the isotopic values is accentuated by the near single-point source of origin. Diesel fuels were obtained from various locations in the South Island of New Zealand. Aliquots of these samples were diluted with n-pentane and subsequently analyzed with gas chromatography-isotope ratio mass spectrometry (GC-IRMS) for carbon and hydrogen isotope values. The data obtained were subjected to principal component analysis (PCA) and hierarchical clustering. A wide range of δ13C and δ2H values were determined for the ubiquitous alkane compounds (the greatest values being −4.5‰ and −40‰, respectively). Based on the isotopic character of the alkanes it is suggested that diesel fuels from different locations were distinguishable and that the key components in the differentiation are the δ2H values of the shorter chain-length alkanes. However, while the stable isotope measurements may provide information to classify a sample at a broad scale, much more detailed information is required on the temporal and spatial variability of diesel compositions. The subtle differences of the stable isotope values within the alkanes of different diesel fuels highlighted the power of CSIA as a means of differentiating petroleum products of different origins, even more so when two or more stable isotopes data are combined. This paper shows that CSIA when used in tandem with multivariate statistical methods can provide suitable tools for source apportionment of hydrocarbons by demonstrating a straightforward approach, thus eliminating lengthy analytical processes.

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heterogeneity,” since it expresses the average variability of the simulated values at the grid nodes. The BGV measures the variability of the grid–node averages. This spatial variability is sensitive, although not exclusively, to the spatial variability of the

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