Identificazione della relazione tra riflettività radar e intensità di precipitazione-Applicazione ad eventi intensi registrati sulla Regione Piemonte

Noti il campo spaziale di riflettività Z [mm3], che è una misura della potenza del segnale di ritorno verso il radar che l’aveva emesso e le misure pluviometriche delle stazioni piemontesi (che sono più di 300), la metodologia proposta consiste nello stimare una relazione di potenza del tipo Z=aR^b applicabile all’intera Regione. Con tale fine si determineranno i coefficienti a e b in modo che sia possibile valutare il campo di precipitazione areale R [mm3/h]. I risultati verranno confrontati con quelli derivanti dall’attuale formula utilizzata da ARPA Piemonte: Z=300R^1.5 (Joss e Waldvoguel, 1970

Ruolo e funzione dell'Assistente sociale in supporto alle donne vittime di reato nel sistema dei servizi territoriali. La specializzazione As.S.Vi.

Negli ultimi anni, il fenomeno della violenza domestica è diventato un problema sociale rilevante nel nostro Paese, a causa di un numero di femminicidi sempre maggiore. Oggigiorno molti casi di cronaca nera sottolineano, molto spesso, l’inadeguatezza della prevenzione, della metodologia di contrasto alla violenza e della tutela garantita alle vittime, troppo spesso lasciate sole dalle istituzioni, specialmente se non sporgono denuncia alle autorità competenti. Proprio da qui è nata l’idea di evidenziare le criticità e le problematiche all’interno del sistema normativo e di politiche sociali pubbliche nell’affrontare casi di violenza domestica, con l’obiettivo di arrivare a formulare procedure e strategie appropriate per riempire quelle lacune evidenziate nel nostro Paese. Dunque, la Tesi ha prodotto una procedura e una strategia sperimentale possibile da attivare ogni qualvolta che una vittima di violenza domestica chiede aiuto e supporto in un servizio pubblico territoriale. Tale strategia condivide molti dei principi fondamentali del Metodo Scotland tra cui la fase del tutoraggio, la valutazione del rischio e la presa in carico multidimensionale. Dunque, la Tesi propone una strategia di supporto e sostegno alle vittime di violenza domestica, introducendo la figura dell’As.S.Vi. e sottolineando la necessità di una valutazione del rischio e di una presa in carico multiprofessionale e multidisciplinare, proprio per evitare il continuo delle violenze e dei femminicidi

Continuous Learning of HPC Infrastructure Models using Big Data Analytics and In-Memory processing Tools

open4siThis work was supported, in parts, by the FP7 ERC Advance project MULTITHERMAN (g.a. 291125), by the EU H2020 FETHPC project ANTAREX (g.a. 67623) and by the EU H2020 FETHPC project Exanode (g.a. 671578).Exascale computing represents the next leap in the HPC race. Reaching this level of performance is subject to several engineering challenges such as energy consumption, equipment-cooling, reliability and massive parallelism. Model-based optimization is an essential tool in the design process and control of energy efficient, reliable and thermally constrained systems. However, in the Exascale domain, model learning techniques tailored to the specific supercomputer require real measurements and must therefore handle and analyze a massive amount of data coming from the HPC monitoring infrastructure. This becomes rapidly a 'big data' scale problem. The common approach where measurements are first stored in large databases and then processed is no more affordable due to the increasingly storage costs and lack of real-time support. Nowadays instead, cloud-based machine learning techniques aim to build on-line models using real-time approaches such as 'stream processing' and 'in-memory' computing, that avoid storage costs and enable fastdata processing. Moreover, the fast delivery and adaptation of the models to the quick data variations, make the decision stage of the optimization loop more effective and reliable. In this paper we leverage scalable, lightweight and flexible IoT technologies, such as the MQTT protocol, to build a highly scalable HPC monitoring infrastructure able to handle the massive sensor data produced by next-gen HPC components. We then show how state-of-the art tools for big data computing and analysis, such as Apache Spark, can be used to manage the huge amount of data delivered by the monitoring layer and to build adaptive models in real-time using on-line machine learning techniques.openBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, LucaBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, Luc

Environmental and Economic Impact of the Antifreeze Agents in Geothermal Heat Exchangers

Borehole heat exchangers (BHEs) generally employ water-antifreeze solutions to allow working fluid temperatures to fall below 0 °C. However, some local regulations have forbidden antifreeze additives (even non-toxic ones) to avoid groundwater pollution in case of pipe leakage. This paper presents a techno-economic and environmental analysis of four different fluids: propylene glycol at 25% and 33% weight concentrations, calcium chloride at 20% weight concentration (CaCl2 20%), and pure water. Thermal loads from 36 case studies in six different climate zones are used to perform BHE sizing and compare the abovementioned fluids from the economic, operational, and environmental points of view. The economic analysis and the carbon footprint assessment are performed on a life cycle of 25 years considering the installation (BHE drilling, fluid) and operation (heat pump and ground-side circulation pump energy demand, fluid replacement) of the simulated GSHPs. Results highlight that using pure water as a heat carrier fluid is convenient for cooling-dominated buildings but, for heating-dominated buildings, this choice leads to a noticeable increase of the BHE needed length which is not compensated by the lower operational costs. On the other hand, avoiding the use of antifreeze additives generally leads to a reduction of the lifetime carbon footprint, with a few exceptions in very cold climates. CaCl2 20% proves to be a good choice in most cases, both from the economic and the environmental points of view, as it allows a strong reduction of the installed BHE length in cold climates with a low additional cost and carbon footprint

Efficiency assessment for a small heliostat solar concentration plant

Summary In this paper, a small non-imaging focusing heliostat is presented, and an analytical model for assessing its performance is described. The main novelty of the system lies in the tracking mechanism and the mirror mount, which are based on off-the-shelf components and allow a good trade-off between accuracy and costs. The concentrator mirrors are moved by this two-axis tracking machinery to reflect the sun's rays onto a fixed target, the dimensions of which can be varied to suit the user's needs. A prototype plant to be located in central Italy was designed and simulated with a ray-tracing algorithm, and it comprises 90 heliostats for a total reflective area of 7.5 m2. The reflected solar rays are tracked taking the mechanical positioning errors of the tracking system into account. The total flux of radiation energy hitting the target was determined, and intensity distribution maps were drawn. Simulations showed that the system's optical efficiency can exceed 90% in summer, despite the tracking errors, mainly because of the smaller distance between the heliostats and the receiver. The solar concentration ratio over a receiver of 250 mm in diameter reached 80 suns with a very good uniformity. Over a 400-mm receiver, the concentrated radiation was less uniform, and the solar concentration ratio reached 50 suns, with a higher optical efficiency and collected solar radiation. The present concentration ratio is still suitable for many applications ranging from the electric power production, industrial process heat, and solar cooling. Copyright © 2014 John Wiley & Sons, Ltd