Deep structure of crust and mantle beneath Iberia and Western Mediterranean from P and S Receiver functions and SKS Waveforms

We have conducted a P and S receiver functions [PRFs and SRFs] analysis for 19 seismic stations on the Iberia and western Mediterranean. In the transition zone [TZ] the PRFs analysis reveals a band [from Gibraltar to Balearic] increased by 10-20 km relative to the standard 250 km. The TZ thickness variations are strongly correlated with the P660s times in PRFs. We interpret the variable depth of the 660-km discontinuity as an effect of subduction. Over the anomalous TZ we found a reduced velocity zone in the upper mantle. Joint inversion of PRFs and SRFs reveals a subcrustal high S velocity lid and an underlying LVZ. A reduction of the S velocity in the LVZ is less than 10%. The Gutenberg discontinuity is located at 65±5 km, but in several models sampling the Mediterranean, the lid is missing or its thickness is reduced to ~30 km. In the Gibraltar and North Africa this boundary is located at ~100 km. The lid Vp/Vs beneath Betics is reduced relative to the standard 1.8. Another evidence of the Vp/Vs anomaly is provided by S410p phase late arrivals in the SRFs. The azimuthal anisotropy analysis with a new technology was conducted at 5 stations and at 2 groups of stations. The fast direction in the uppermost mantle layer is ~90º in Iberian Massif. In Balearic is in the azimuth of ~120º. At a depth of ~60 km the direction becomes 90º. Anisotropy in the upper layer can be interpreted as frozen, whereas anisotropy in the lower layer is active, corresponding to the present-day or recent flow. The effect of the asthenosphere in the SKS splitting is much larger than the effect of the subcrustal lithosphere.

PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

Comparing wind generation profiles: A circular data approach

The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.