Buoyancy-induced convection of water-based nanofluids in differentially-heated horizontal Semi-Annuli

A two-phase model based on the double-diffusive approach is used to perform a numerical study on natural convection of water-based nanofluids in differentially- heated horizontal semi-annuli, assuming that Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. The system of the governing equations of continuity, momentum, and energy for the nanofluid, and continuity for the nanoparticles, is solved by the way of a computational code which incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity, and the thermophoretic diffusion coefficient, all based on a wide number of literature experimental data. The pressure-velocity coupling is handled through the SIMPLE-C algorithm. Numerical simulations are executed for three different nanofluids, using the diameter and the average volume fraction of the suspended nanoparticles, the cavity size, the average temperature, and the temperature difference imposed across the cavity, as independent variables. It is found that the impact of the nanoparticle dispersion into the base liquid increases remarkably with increasing the average temperature, whereas, by contrast, the other controlling parameters have moderate effects. Moreover, at temperatures of the order of room temperature or just higher, the heat transfer performance of the nanofluid is significantly affected by the choice of the solid phase material

Natural convection from a pair of differentially-heated horizontal cylinders aligned side by side in a nanofluid-filled square enclosure

A two-phase model based on the double-diffusive approach is used to perform a numerical study on natural convection from a pair of differentially-heated horizontal cylinders set side by side in a nanofluid-filled adiabatic square enclosure. The study is conducted under the assumption that Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. The system of the governing equations of continuity, momentum and energy for the nanofluid, and continuity for the nanoparticles, is solved by the way of a computational code which incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity, and the thermophoretic diffusion coefficient, all based on a wide number of literature experimental data. The pressure-velocity coupling is handled through the SIMPLE-C algorithm. Simulations are executed for three different nanofluids, using the diameter and the average volume fraction of the suspended nanoparticles, as well as the cavity width, the inter-cylinder spacing, the average temperature of the nanofluid, and the temperature difference imposed between the cylinders, as controlling parameters, whose effects are thoroughly analyzed and discussed. It is found that the impact of the nanoparticle dispersion into the base liquid increases remarkably with increasing the average temperature, whereas it increases just moderately as the nanoparticle size decreases, as well as the imposed temperature difference and the cavity width increase. Conversely, the distance between the cylinders seems to have marginal effects. Moreover, an optimal particle loading for maximum heat transfer is detected for most configurations investigated

Buoyancy-induced convection of water-based nanofluids in differentially-heated horizontal Semi-Annuli

A two-phase model based on the double-diffusive approach is used to perform a numerical study on natural convection of water-based nanofluids in differentially- heated horizontal semi-annuli, assuming that Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. The system of the governing equations of continuity, momentum, and energy for the nanofluid, and continuity for the nanoparticles, is solved by the way of a computational code which incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity, and the thermophoretic diffusion coefficient, all based on a wide number of literature experimental data. The pressure-velocity coupling is handled through the SIMPLE-C algorithm. Numerical simulations are executed for three different nanofluids, using the diameter and the average volume fraction of the suspended nanoparticles, the cavity size, the average temperature, and the temperature difference imposed across the cavity, as independent variables. It is found that the impact of the nanoparticle dispersion into the base liquid increases remarkably with increasing the average temperature, whereas, by contrast, the other controlling parameters have moderate effects. Moreover, at temperatures of the order of room temperature or just higher, the heat transfer performance of the nanofluid is significantly affected by the choice of the solid phase material

Egalitarianism in the rank aggregation problem: a new dimension for democracy

Winner selection by majority, in an election between two candidates, is the only rule compatible with democratic principles. Instead, when the candidates are three or more and the voters rank candidates in order of preference, there are no univocal criteria for the selection of the winning (consensus) ranking and the outcome is known to depend sensibly on the adopted rule. Building upon XVIII century Condorcet theory, whose idea was to maximize total voter satisfaction, we propose here the addition of a new basic principle (dimension) to guide the selection: satisfaction should be distributed among voters as equally as possible. With this new criterion we identify an optimal set of rankings. They range from the Condorcet solution to the one which is the most egalitarian with respect to the voters. We show that highly egalitarian rankings have the important property to be more stable with respect to fluctuations and that classical consensus rankings (Copeland, Tideman, Schulze) often turn out to be non optimal. The new dimension we have introduced provides, when used together with that of Condorcet, a clear classification of all the possible rankings. By increasing awareness in selecting a consensus ranking our method may lead to social choices which are more egalitarian compared to those achieved by presently available voting systems.Comment: 18 pages, 14 page appendix, RateIt Web Tool: http://www.sapienzaapps.it/rateit.php, RankIt Android mobile application: https://play.google.com/store/apps/details?id=sapienza.informatica.rankit. Appears in Quality & Quantity, 10 Apr 2015, Online Firs

Experimental tests of solar collectors prototypes systems

Solar thermal collectors represent one of the most widely used technologies for heat production from renewable energy sources. To increase efficiency and to not increase too much cost different type of solar collectors, and in particular of evacuated tube collectors have been realized. In order to compare performance, tests at different conditions and in different configurations have to be performed. The aim of this paper is to establish the performance of a new prototype via an experimental evaluation of the performance in different conditions and configurations of three collectors. The prototype is particular owing to his new head configuration that permits an innovative parallel configuration way. Therefore, parallel and series configurations have been analyzed applying the UNI-EN 12975, in a steady-state regime. The efficiencies of the two configurations have been tested for different flow rates and different inflow water temperatures. The experimental results show that, with the same input flow rate to the single collector, the parallel configuration has higher performance than the series one, reaching 15% higher level of efficiency. Thus, it seems that these prototypes in optimized configuration can lead to a systems improvement, thereby increasing the overall energy production or giving the same energy production with smaller collector area. © 2015 Published by Elsevier Ltd

Dragon: Multidimensional Range Queries on Distributed Aggregation Trees,

Distributed query processing is of paramount importance in next-generation distribution services, such as Internet of Things (IoT) and cyber-physical systems. Even if several multi-attribute range queries supports have been proposed for peer-to-peer systems, these solutions must be rethought to fully meet the requirements of new computational paradigms for IoT, like fog computing. This paper proposes dragon, an ecient support for distributed multi-dimensional range query processing targeting ecient query resolution on highly dynamic data. In dragon nodes at the edges of the network collect and publish multi-dimensional data. The nodes collectively manage an aggregation tree storing data digests which are then exploited, when resolving queries, to prune the sub-trees containing few or no relevant matches. Multi-attribute queries are managed by linearising the attribute space through space lling curves. We extensively analysed dierent aggregation and query resolution strategies in a wide spectrum of experimental set-ups. We show that dragon manages eciently fast changing data values. Further, we show that dragon resolves queries by contacting a lower number of nodes when compared to a similar approach in the state of the art

Study of dental implant titanium surface: Nanotechnology in new surfaces evaluation relating to jaws osseointegration.

Il presente lavoro parte dalla descrizione dei processi di rimodellamento osseo mascellare a seguito della perdita di elementi dentari e la successiva riabilitazione mediante impianto dentale osteointegrato. Approfondiremo proprio i complessi aspetti dell’osteointegrazione su superfici implantari in titanio sia a livello micro che macroscopico. Nel campo dell’implantologia, infatti, il titanio risulta essere il materiale maggiormente impiegato in virtù della sua eccellente biocompatibilità e resistenza. Successivamente prenderemo in analisi i trattamenti di superficie implantare ad oggi più diffusi, lavorati prevalentemente a livello microscopico e infine confronteremo una sistematica trattata tradizionalmente con una innovativa trattata superficialmente a livello nanometrico. Il confronto avverrà in vivo, paragonando i risultati ottenuti clinicamente e radiograficamente tra le 2 sistematiche implantari, utilizzate per ripristinare la funzione masticatoria nei pazienti arruolati.This paper starts from the description of the processes of the maxillary bone remodeling due to the loss of teeth and the subsequent rehabilitation by osseointegrated dental implants. We are deepening the complex features of osseointegration of titanium implant surfaces at both micro and macroscopic aspects. In fact in implantology the titanium appears to be the material most widely used because of its excellent biocompatibility and resistance. Subsequently we will analyze the implant surface treatments for today's most popular, worked mostly at the microscopic level and then will compare a treated traditionally system with an innovative surface treated at the nanometer level. The comparison will take place in vivo, by comparing the results obtained clinically and radiographically between the two implant systems, used to restore the masticatory function in patients enrolled

Distributed Current Flow Betweeness Centrality

—The computation of nodes centrality is of great importance for the analysis of graphs. The current flow betweenness is an interesting centrality index that is computed by considering how the information travels along all the possible paths of a graph. The current flow betweenness exploits basic results from electrical circuits, i.e. Kirchhoff’s laws, to evaluate the centrality of vertices. The computation of the current flow betweenness may exceed the computational capability of a single machine for very large graphs composed by millions of nodes. In this paper we propose a solution that estimates the current flow betweenness in a distributed setting, by defining a vertex-centric, gossip-based algorithm. Each node, relying on its local information, in a selfadaptive way generates new flows to improve the betweenness of all the nodes of the graph. Our experimental evaluation shows that our proposal achieves high correlation with the exact current flow betweenness, and provides a good centrality measure for large graphs

A Study on the Impact of Climate Adaptive Building Shells on Indoor Comfort

Energy savings and indoor comfort are widely considered to be key priorities in the current architectural design trends. Additionally, the well-being and satisfaction of end users is a relevant issue when a human-centred perspective is adopted. The application of Climate Adaptive Building Shells (CABS) compared to conventional façades offers appropriate opportunities for tackling these challenges. This paper reports the outcomes of a study performed on CABS in order to optimise the indoor comfort while calibrating the configuration of a dynamic façade module. The horizontal louvres of the adaptive façade are moved by an actuator that exploits the expansion of a thermo-active resin as it melts, by its absorption of energy. The actuation mechanism depends on the outdoor air temperature conditions and does not require a supply of energy. The performed simulation evidenced a decrease of approximately 4°C indoors when the dynamic module is fully efficient (21st June at 12 p.m.). Furthermore, the lux level is always within the comfort range for an office building (500-2000 lux) during both winter and summer scenarios. The optimised solution shows a substantial gain for energy performance and environmental sustainability. Moreover, the uniformity of distribution of daylight illuminance across the entire space is another associated advantage, giving interesting insights into potentials for architectural façade design

Multiparameter quantum estimation of noisy phase shifts

Phase estimation is the most investigated protocol in quantum metrology, but its performance is affected by the presence of noise, also in the form of imperfect state preparation. Here we discuss how to address this scenario by using a multiparameter approach, in which noise is associated to a parameter to be measured at the same time as the phase. We present an experiment using two-photon states, and apply our setup to investigating optical activity of fructose solutions. Finally, we illustrate the scaling laws of the attainable precisions with the number of photons in the probe state