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This paper deals with some aspects of the mining prospection of clays in the South of Córdoba (Spain). That studied clays are used as raw materials in a processing plant of ceramic products. In this ground characterisation for future mining operations, low proportion of carbonated materials was searched. To carry out the study, three seek areas were defined, each one of them of about 4 Km2, where two geophysical methods were applied (Electrical Resistivity Tomography and Vertical Electrical Sounding). X-ray diffraction, EDAX, direct cut, compaction, swelling and bearing capacity tests, among others, were carried out in samples picked up in each seek area. Using the information provided by all these tests the most interesting areas for the exploitation defined. These studies resulted in the selection of new interesting deposits for the clay industry.El presente trabajo trata de la exploración de arcillas con baja proporción de calcita, en el sur de la provincia de Córdoba, para suministrar materias primas a la fabricación de bloques y productos cerámicos. Para la caracterización del subsuelo se han planificado tres zonas de trabajo de 4 km2 cada una, en las que se han aplicado métodos geofísicos basados en perfiles de Tomografía Eléctrica y Sondeos Eléctricos Verticales (SEV). En muestras de cada zona se han realizado análisis mineralógicos de difracción de rayos-X (DRX), análisis químico por energías dispersivas de rayos-X (EDAX), ensayos de plasticidad, corte directo, compactación, hinchamiento y capacidad portante, molienda, secado y cocción. Se ha conseguido descubrir, en estas zonas, las áreas de interés para la explotación de materias primas, y con los resultados de esta prospección pueden estudiarse nuevos yacimientos de arcilla cerámica.

This paper summarizes the results of applying cooperative and project-based learning strategies in two different engineering courses in order to explore their benefits in the students' self-perceptions of project management skills. Nine technical skills and four behavioural ones were evaluated during the academic years 2012 13 and 2013-14 in Civil Engineering, and 2014 15 and 2015-16 in Forest Engineering courses (117 students). The first strategy consisted of the preparation of a project plan to solve a customer's request and the second one was the drafting of a Facebook page to promote one specific commercial project. Results from this study show the strong improvement observed in all the skills studied, these self-rating increases were statistically significant in most of them by the end of the courses. Different tests were applied in order to appropriately assess statistical significance depending on self-rating data distribution. This work confirms the benefit of the application of cooperative and project-based learning strategies on self-perceived improvement in the students' project management skills in engineering courses. These findings are of considerable interest to engineering institutions that want to advance in favour of the students' perceptions of competence and they serve to deepen the combined effects of cooperative and project-based learning in higher education. [ABSTRACT FROM AUTHOR]

The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions ( γmax and K(0)) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this work, the multifractal properties of hourly rainfall data recorded at a location in Southern Spain have been related to the scale properties of the corresponding intensity-duration-frequency (IDF) curves. Four parametric models for the IDF curves have been fitted to the quantiles of rainfall obtained using the generalized Pareto frequency distribution function with the extreme data series obtained for the same place. The scaling of the rainfall intensity moments has been analysed, and the empirical moments scaling exponent function has been obtained. The corresponding values of q1 and γ1 have been empirical and theoretically calculated and compared with some characteristics of the different IDF models. Thus, the scaling behaviour of IDF curves has been analysed, and the best model has been selected. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article discusses the validation of a rainfall model through the application of a multifractal analysis. In a study of the Iberian Peninsula, a multifractal analysis was done to validate the simulation of rainfall records. Four locations in Andalusia in Southern Spain were observed, where simulated hourly rainfall was carried out. The location was observed in 4-year and 20-year durations in order to determine the influence of the length of the data series. The results of the study indicated that algebraic tails are needed to fit the probability distribution for extreme events of rain. Also, dry event durations were seen to fit when real and synthetic data are taken into consideration. A count-based periodogram and the Fano factor methods were applied in a time clustering analysis.

Multifractal properties of 30 min wind data series recorded at six locations in Cadiz (Southern Spain) have been studied in this work with the aim of obtaining detailed information for a range of time scales. Wind speed records have been validated, applying various quality control tests as a pre-requisite before their use, improving the reliability of the results due to the identification of incorrect values which have been discarded in the analysis. The scaling of the wind speed moments has been analysed and empirical moments scaling exponent functions K(q) have been obtained. Although the same critical moment (qcrit) has been obtained for all the places, some differences appear in other multifractal parameters like γmax and the value of K(0). These differences have been related to the presence of extreme events and zero data values in the data series analysed, respectively. [ABSTRACT FROM AUTHOR]

Since the last century, the air surface temperature has increased at a global scale, showing trends and inhomogeneities that vary from place to place. Many statistical methods can be used to analyze whether or not an inhomogeneity or break point exists in a meteorological data series, and even to detect the time of the break. Sometimes, there is no agreement in the year at which the inhomogeneity occurs detected by different tests. The scale invariance of a process can be studied through its multifractal properties that can be related to the existence of break points in it. In this work, the multifractal properties of monthly temperature data series are used to test what is the right break point year in those situations at which different dates are found by two different tests: the Pettitt and the Standard Normal Homogeneity tests. The comparison of the fractal dimension function D q and the multifractal spectrum obtained by the box counting method for both the original data sets and for those obtained by splitting the original into two considering the break point years was made. When different multifractal functions and parameters were obtained, a break point was confirmed. Whereas, if equal values appeared, the break point year was discarded. These results let to select the most suitable test to be applied to detect inhomogeneities in a certain data set that will be very useful for climate change studies.