This paper presents applications of the peaks-over threshold methodology for both the univariate and the recently introduced bivariate case, combined with a novel bootstrap approach. We compare the proposed bootstrap methods to the more traditional profile likelihood.We have investigated 63 years of the European Climate Assessment daily precipitation data for five Hungarian grid points, first separately for the summer and winter months, then aiming at the detection of possible changes by investigating 20 years moving windows. We show that significant changes can be observed both in the univariate and the bivariate cases, the most recent period being the most dangerous, as the return levels here are the highest. We illustrate these effects by bivariate coverage regions.Keywords daily precipitation data · moving window · profile likelihood · return level · univariate and bivariate generalized Pareto distribution · weighted bootstrap 1 IntroductionDetection of signs for climate changes are in the focus of recent climatology. There is an abundance of publications in the area of temperature changes. Precipitation is equally important, if we consider its economic effect -here the extremes play an especially important role, since these are in

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The objective of this work is the mechanical characterization of materials produced by 3D printing based on Fused Deposition Modelling (FDM®). The materials chosen are various poly(lactic acid) (PLA) bases reinforced with another material (e. g. glass fiber, metal powder, ….) in different weight fractions. In view of the FDM technique, producing specimens layer by layer and following predefined orientations, the main assumption considered is that the materials behave similarly to laminates formed by orthotropic layers. Great emphasis must be put on the selection of the appropriate quality filaments, therefore first the material properties of the fibers were examined. Following tensile strength tests, scanning electron microscopy (SEM) was employed to observe fracture surfaces. It was clear from the microstructure of the filaments that the morphology of the fibers are material dependent. This difference as well as the diverse types of the fibers explains the variability in material properties among the test materials examined.

The automotive industry is one of the most important customers for the foundry industry. In particular, casting of engine parts for combustion engines is one of the most demanding areas of casting technology. New generation of engine blocks and cylinder heads are getting geometrically more complicated in order to maintain or even increase performance. With the increased complexity, the strain for the casting molds is growing and the widely used technology of core making with standard silica sands is, for several applications, no longer reaching the demanded results. Furthermore, in last decade, there has been an effort in using inorganic binders in core making process, which brings along some additional technological challenges. In order to cope with these challenges, in this paper, silica and non-silica sands with round and angular grains as well as with fine and coarse grains are examined using an inorganic binder for strength, permeability, and thermal stability. The results shall provide useful information about the possibilities of application and combining different types of foundry sands, both silica and non-silica. With their impact on the selected sand core properties, they can help in solving problems in the core making process as well as reaching a high quality of the final product-casting.

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Abstract.In an earlier paper, Rakonczai et al. (2014) emphasised the importance of investigating the effective sample size in case of autocorrelated data. The simulations were based on the block bootstrap methodology. However, the discreteness of the usual block size did not allow for exact calculations. In this paper we propose a new generalisation of the block bootstrap methodology, which allows for any positive real number as expected block size. We relate it to the existing optimisation procedures and apply it to a temperature data set. Our other focus is on statistical tests, where quite often the actual sample size plays an important role, even in the case of relatively large samples. This is especially the case for copulas. These are used for investigating the dependencies among data sets. As in quite a few real applications the time dependence cannot be neglected, we investigated the effect of this phenomenon on the used test statistic. The critical value can be computed by the proposed new block bootstrap simulation, where the block size is determined by fitting a VAR model to the observations. The results are illustrated for models of the used temperature data.

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means of different methods: electron probe microanalysis (EPMA), transmission electron microscopy (TEM), electron diffraction (ED), energy dispersive X-ray analysis (EDX) and X-ray diffraction (XRD). The presence of the intermetallic phases confirmed that phase forming solid state reactions start during the mechanofusion treatment.