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Bioactivity, mechanical properties and drug delivery ability of bioactive glass-ceramic scaffolds coated with a natural-derived polymer
No full textCFD simulations to optimize the blade design of water wheels
No full textAt low head sites and at low discharges, water wheels can be considered among the most convenient hydropower converters to install. The aim of this work is to improve the performance of an existing breastshot water wheel by changing the blade shape using computational fluid dynamic (CFD) simulations. Three optimal profiles are investigated: the profile of the existing blades, a circular profile and an elliptical profile. The results are validated by performing experimental tests on the wheel with the existing profile. The numerical results show that the efficiency of breastshot wheels is affected by the blade profile. The average increase in efficiency using the new circular profile is about 4 % with respect to the profile of the existing blades
Design and Optimization of Graph Transform for Image and Video Compression
No full textThe main contribution of this thesis is the introduction of new methods for designing adaptive transforms for image and video compression. Exploiting graph signal processing techniques, we develop new graph construction methods targeted for image and video compression applications. In this way, we obtain a graph that is, at the same time, a good representation of the image and easy to transmit to the decoder. To do so, we investigate different research directions. First, we propose a new method for graph construction that employs innovative edge metrics, quantization and edge prediction techniques. Then, we propose to use a graph learning approach and we introduce a new graph learning algorithm targeted for image compression that defines the connectivities between pixels by taking into consideration the coding of the image signal and the graph topology in rate-distortion term. Moreover, we also present a new superpixel-driven graph transform that uses clusters of superpixel as coding blocks and then computes the graph transform inside each region. In the second part of this work, we exploit graphs to design directional transforms. In fact, an efficient representation of the image directional information is extremely important in order to obtain high performance image and video coding. In this thesis, we present a new directional transform, called Steerable Discrete Cosine Transform (SDCT). This new transform can be obtained by steering the 2D-DCT basis in any chosen direction. Moreover, we can also use more complex steering patterns than a single pure rotation. In order to show the advantages of the SDCT, we present a few image and video compression methods based on this new directional transform. The obtained results show that the SDCT can be efficiently applied to image and video compression and it outperforms the classical DCT and other directional transforms. Along the same lines, we present also a new generalization of the DFT, called Steerable DFT (SDFT). Differently from the SDCT, the SDFT can be defined in one or two dimensions. The 1D-SDFT represents a rotation in the complex plane, instead the 2D-SDFT performs a rotation in the 2D Euclidean space
Analog Models Manipulation for Effective Integration in Smart System Virtual Platforms
No full textAnalog components are fundamental blocks of smart systems, as they allow a tight interaction with the environment, in terms of both sensing/actuation and communication. This impacts on the design of the overall system, and mainly on the validation phase, that thus requires the joint simulation of digital and analog aspects. In this scenario, this paper proposes the automatic conversion of analog models to C++-based languages, to remove the overhead of co-simulation with traditional virtual platform tools. The proposed methodology allows to convert a given analog description to either (1) a fully equivalent description, or (2) an abstract representation for faster simulation which models only the aspects of interest. Effectiveness and correctness have been proved on a number of case studies, that highlight the effectiveness and potentiality of the proposed methodology
Time-average velocity estimation through surface-wave analysis: Part 2 - P-wave velocity
No full textSurface waves (SWs) in seismic records can be used to extract local dispersion curves (DCs) along a seismic line. These curves can be used to estimate near-surface S-wave velocity models. If the velocity models are used to compute S-wave static corrections, the required information consists of S-wave time-average velocities that define the one-way time for a given datum plan depth. However, given the wider use of P-wave reflection seismic with respect to S-wave surveys, the estimate of P-wave time-average velocity would be more useful. We therefore focus on the possibility of also extracting time-average P-wave velocity models from SW dispersion data.We start from a known 1D S-wave velocity model along the line, with its relevant DC, and we estimate a wavelength/depth relationship for SWs.We found that this relationship is sensitive to Poisson's ratio, and we develop a simple method for estimating an "apparent" Poisson's ratio profile, defined as the Poisson's ratio value that relates the time-average S-wave velocity to the time-average P-wave velocity. Hence, we transform the time-average S-wave velocity models estimated from the DCs into the time-average P-wave velocity models along the seismic line. We tested the method on synthetic and field data and found that it is possible to retrieve time-average P-wave velocity models with uncertainties mostly less than 10% in laterally varying sites and one-way traveltime for P-waves with less than 5 ms uncertainty with respect to P-wave tomography data. To our knowledge, this is the first method for reliable estimation of P-wave velocity from SW data without any a priori information or additional data
A Novel Method for Online Detection of Faults Affecting Execution-Time in Multicore-Based Systems
No full textThis article proposes a bounded interference method, based on statistical evaluations, for online detection and tolerance of any fault capable of causing a deadline miss. The proposed method requires data that can be gathered during the profiling and worst-case execution time (WCET) analysis phase. This article describes the method, its application, and then it presents an avionic mixed-criticality use case for experimental evaluation, considering both dual-core and quad-core platforms. Results show that faults that can cause a timing violation are correctly identified while other faults that do not introduce a significant temporal interference can be tolerated to avoid high recovery overheads
Foreword: Special Section on Addressing Signal and Power Integrity in Future Generation Systems—Part I: Technology and Design Considerations
No full textLow-noise and wide-bandwidth current readout at low temperatures using a superconducting-quantum-interference-device amplifier
No full textWe report on the development of a current amplifier for measuring small currents from mesoscopic electronic devices at low temperatures down to the milli-Kelvin range. In our setup, a superconducting quantum interference device (SQUID) located at the mixing chamber stage of the dilution refrigerator is used as the first-stage current amplifier, thereby improving the noise floor down to 8 ' 10%27A2/Hz, which is one order of magnitude as low as those obtained by the conventional methods that utilize a semiconductor-based cryogenic current amplifier. We show the configuration of this setup and demonstrate the amplification of the current generated by a quantum point contact. This approach can open a new way to examine solid-state phenomena that are elusive owing to their small current
Advances in the space-time analysis of rainfall extremes
No full textStatistical estimation of design rainfall is considered a consolidated topic in hydrology. However, extreme rainfalls and their consequences still constitute one of the most critical natural risks worldwide, particularly in urban environments. Additional efforts for improving the spatio-temporal analysis of extreme rainfalls are then required, particularly at the regional scale. In this work, a new set of data and techniques for improving the spatial statistical analysis of extreme rainfall is proposed. Italy is considered a challenging case study, due to its specific geographic and orographic settings, associated with recurring storm-induced disasters. At first, the rain-gauge data patchiness resulting from the evolution of the monitoring agencies and networks, is tackled with the "patched kriging" methodology. The technique, involving a sequential annual interpolation, provides complete annual maxima series consistent with the available data. This allows to extract all the information avaialble from the gauge records, considering also the information "hidden" in the shortest series, increasing the robustness of the results. Interpolation techniques, however, can only reflect the estimation variance determined by the spatial and temporal data resolution. Additional improvements can be obtained integrating the rain gauge information with remote sensing products, able to provide more details on the spatial structure of rainstorms. In this direction, a methodology aimed at maximizing the efficiency of weather radar when dealing with large rainfall intensities is developed. It consists in a quasi-real-time calibration procedure, adopting confined spatial and temporal domains for an adaptive estimation of the relation between radar reflectivity and rainfall rate. This allows one to follow the well-known spatio-temporal variability of the reflectivity-rainfall relation, making the technique suitable for a systematic operational use, regardless of the local conditions. The methodology, applied in a comprehensive case study reduces the bias and increases the accuracy of the radar-based estimations of severe rainfall intensities. The field of the satellite estimation of preciptation is then explored, by analyzing the ability of both the Tropical Rainfall Measurement Mission (TRMM) and the recently launched Global Precipitation Measurement (GPM) mission to help identifying the timing of severe rainfall events on wide spatial domains. For each considered product, the date of occurrence of the most intense annual daily records are identified and compared with the ones extracted from a global rain-gauge database. The timing information can help in tracking the pattern of deep convective systems and support the identification of localized rainfall system in poorly gauged areas. The last part of the work deals with the analysis of rainfall extremes at the country scale, with a particular focus on the most severe rainfall events occurred in Italy in the last century. Many of these events have been studied as individual case studies, due to the large recorded intensities and/or to their severe consequences, but they have been seldom expressly addressed as a definite population. To try to provide new insights in a data-drived approach, a comprehensive set of annual rainfall maxima has been compiled, collecting data from the different regional authorities in charge. The database represents the reference knowledge for extremes from 1 to 24 hours durations in Italy, and includes more than 4500 measuring points nationwide, with observation spanning the period 1916-2014. Exploratory statistical analyses for providing information on the climatology of extreme rainfall at the national scale are carried out and the stationarity in time of the highest quantiles is analysed by pooling up all the data for each duration together. The cumulative empirical distributions are explored looking for clues of the existence of a class of "super-extremes" with a peculiar statistical behavior. The analysis of the spatial the distribution of the records exceeding the 1/1000 overall empirical probability shows an interesting spatial clustering. However, once removed the influence of the uneven density of the rain gauge network in time and space, the spatial susceptibility to extraordinary events seems quite uniformly distributed at the country scale. The analyses carried out provide quantitative basis for improving the rainstorm estimation in gauged and ungauged locations, underlining the need of further research efforts for providing maps for hydrological design with uniform reliability at the various scales of technical interest
Dynamic thermal-hydraulic modelling of the EU DEMO WCLL breeding blanket cooling loops
No full textA global thermal-hydraulic model of the EU DEMO tokamak, based on an object-oriented approach using the Modelica language, is currently under development at Politecnico di Torino. The first module of the global model will simulate the dynamics of the blanket cooling system and it will be able to investigate different coolant options and different cooling schemes, adapted to the different blanket systems currently under development in the Breeding Blanket project. Following the development of the module related to the Helium-Cooled Pebble Bed blanket, this paper presents the dynamic model of the Water-Cooled Lithium Lead (WCLL) blanket, designed at ENEA Brasimone, together with the first results obtained in steady-state condition