In this paper we will demonstrate the use and efficiency of the bootstrap on a geologic problem. The tools of classical statistics are often not applicable because they strongly depend on certain conditions that are not fulfilled. Explicit mathematical formulas for standard errors and confidence intervals with respect to a parameter either require some specific (generally normal) distribution, or they do not exist at all. Hypothesis tests may also only be carried out if some conditions are satisfied. Using the bootstrap method one can simulate the unknown distribution of an arbitrary statistic by its bootstrap replicates; hence any characteristics (standard error, confidence intervals, and test significance levels) can be obtained through direct empirical calculations. We applied the bootstrap to the chemical composition data of rock samples from the Boda Claystone Formation, Hungary. First we investigated the distribution of 8 chemical components in a rock sample group of few elements, computing standard errors and confidence intervals for the mean, the standard deviation and the skewness of these distributions. Then two groups of rock samples from different sampling regions were compared using hypothesis tests.
Upon completion, the National Radioactive Waste Repository in Bátaapáti will provide safe storage for low- and medium-level radioactive waste. The emplacement chambers were excavated in a fractured, blocky, granitic rock mass approximately 240 m below surface. One of the tasks related to the repository development is the feasibility demonstration of the permanent repository closure, including long-term rock mass associated issues. The required lifetime exceeds the usual one of an engineering structure. The long-term behavior of the repository needs to be extrapolated from observation over a shorter time period, or from analogous natural caverns. Numerical methods are the most promising techniques to carry out the extrapolation. It is commonly understood that there are significant uncertainties in long-term predictions. Uncertainties can be mitigated by utilizing independent methods to assess long-term behavior and by improving the prediction capability of the calculation model in the short term. The aim of the paper is to: (1) create a numerical model to effectively capture a wide range of the observed behavior of the rock mass, including tunnel-excavation-induced stress change and stress-dependent permeability and (2) identify the possible cause of long-term creep and show that the long-term creep can be captured by the selected calculation method. The moderately fractured rock mass is modeled using the Universal Distinct Element Code, released by Itasca. The joints in the rock mass are explicitly modeled; the blocky nature of the rock mass is captured. The model is verified with actual field observations and monitoring results. Based on the predicted stress state of the rock mass, the potential cause of long-term creep is identified. By fulfilling the two aims explained above, it is concluded that the model can be used to extrapolate in time and serve as a possible estimation method for the long-term behavior of the repository.
) Parameters of the selected model. (B) Explicit form of the selected model. (C) Parameters of the ARIMA chart. (D) ARIMA chart with the indication of the necessary (minimum) number of realizations
In the practice of SPC
Authors:Dorottya Kovács, Gergely Dabi, and Balázs Vásárhelyi
, and • dip direction and dip angle data can be given as an explicit set of data pairs instead of a distribution function.
For the automatization of data retrieval, a sequence of image-processing operations and algorithms was developed (Fig. 1
Authors:Zsófia Pálos, István János Kovács, Dávid Karátson, Tamás Biró, Judit Sándorné Kovács, Éva Bertalan, Anikó Besnyi, György Falus, Tamás Fancsik, Martina Tribus, László Előd Aradi, Csaba Szabó, and Viktor Wesztergom
assess magmatic water contents using micro-FTIR spectrometry in plagioclase crystals. In this study, “water” and “structural hydroxyl” contents in NAMs are always expressed as molecular water equivalent in wt. ppm if it is not explicitly otherwise