Pollutant emissions in common-rail diesel engines in extraurban cycle: rapeseed oils vs diesel fuel

The new energy strategy of EU (i.e., Directive 2009/28/EC) requires increasing the use of biofuels in transports up to at least 10% of the total fuel consumption. In the last years, the share of Diesel engines in automotive applications reached about 55% in EU market, thus trying to widen the alternatives to Diesel fuel is very important. In this framework straight vegetable oils (SVO) can represent one of the available possibilities at least in some specific applications (i.e., public transportation, hybrid or marine propulsion, etc.). SVO properties may be very different form Diesel fuel, thus operating a Diesel engine with SVO might result in some problems, especially in automotive configuration where the electronic unit acts as if it is working with Diesel fuel. This reflects in possible engine power and torque reduction, maintenance problems, and pollutant emissions during vehicles running. The latter aspect is the focus of the present paper. In this work, we used a turbocharged, four stroke, four cylinders, water cooled, commonrail multijet Diesel engine in automotive configuration to simulate the extraurban cycle according to the EU standard, comparing pollutant emissions in case of SVO and gasoil fuelling

Internal combustion engine sensor network analysis using graph modeling

In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data. In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs. The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis

Properties of bars in the local universe

We studied the fraction and properties of bars in a sample of about 3000 galaxies extracted from SDSS-DR5. This represents a volume limited sample with galaxies located between redshift 0.01-20, and inclination i < 60. Interacting galaxies were excluded from the sample. The fraction of barred galaxies in our sample is 45%. We found that 32% of S0s, 55% of early-type spirals, and 52% of late-type spirals are barred galaxies. The bars in S0s galaxies are weaker than those in later-type galaxies. The bar length and galaxy size are correlated, being larger bars located in larger galaxies. Neither the bar strength nor bar length correlate with the local galaxy density. On the contrary, the bar properties correlate with the properties of their host galaxies. Galaxies with higher central light concentration host less and weaker bars.Comment: 2 pages, 1 figure to appear in the proceedings of "Formation and Evolution of Galaxy Disks", Rome, October 2007, Eds. J. Funes and E. M. Corsin

Energy rating of a water pumping station using multivariate analysis

Among water management policies, the preservation and the saving of energy demand in water supply and treatment systems play key roles. When focusing on energy, the customary metric to determine the performance of water supply systems is linked to the definition of component-based energy indicators. This approach is unfit to account for interactions occurring among system elements or between the system and its environment. On the other hand, the development of information technology has led to the availability of increasing large amount of data, typically gathered from distributed sensor networks in so-called smart grids. In this context, data intensive methodologies address the possibility of using complex network modeling approaches, and advocate the issues related to the interpretation and analysis of large amount of data produced by smart sensor networks. In this perspective, the present work aims to use data intensive techniques in the energy analysis of a water management network. The purpose is to provide new metrics for the energy rating of the system and to be able to provide insights into the dynamics of its operations. The study applies neural network as a tool to predict energy demand, when using flowrate and vibration data as predictor variables

The influence of water desalination systems on load levelling of gen-set in small off-grid islands

In minor off-grid islands, energy is typically supplied by diesel generator set, while water, when not shipped with water tankers, is produced by means of desalination systems (typically based on reverse osmosis). The additional demand of desalination related power to the already inefficient diesel power systems may worsen gen-set performance. State-of-the-art remedial strategies advocate the use of renewable energy technologies in order to reduce the impact on diesel generators. Nevertheless, many small islands, due to their environmental value and tourist vocation or due to the quality of the local grid, do suffer of more stringent limitations reducing the potential of penetration of renewable energy. To this end, the present work aims at reporting on the influence of water desalination system on diesel generators load levelling. The study of different matching scenario, using a time-dependent model, demonstrates the possibility of finding management strategy paying-off with improved generator performance

Structural properties of disk galaxies I. The intrinsic ellipticity of bulges

(Abridged) A variety of formation scenarios was proposed to explain the diversity of properties observed in bulges. Studying their intrinsic shape can help in constraining the dominant mechanism at the epochs of their assembly. The structural parameters of a magnitude-limited sample of 148 unbarred S0--Sb galaxies were derived in order to study the correlations between bulges and disks as well as the probability distribution function (PDF) of the intrinsic equatorial ellipticity of bulges. It is presented a new fitting algorithm (GASP2D) to perform the two-dimensional photometric decomposition of galaxy surface-brightness distribution. This was assumed to be the sum of the contribution of a bulge and disk component characterized by elliptical and concentric isophotes with constant (but possibly different) ellipticity and position angles. Bulge and disk parameters of the sample galaxies were derived from the J-band images which were available in the Two Micron All Sky Survey. The PDF of the equatorial ellipticity of the bulges was derived from the distribution of the observed ellipticities of bulges and misalignments between bulges and disks. Strong correlations between the bulge and disk parameters were found. About 80% of bulges in unbarred lenticular and early-to-intermediate spiral galaxies are not oblate but triaxial ellipsoids. Their mean axial ratio in the equatorial plane is = 0.85. There is not significant dependence of their PDF on morphology, light concentration, and luminosity. The interplay between bulge and disk parameters favors scenarios in which bulges assembled from mergers and/or grew over long times through disk secular evolution. But all these mechanisms have to be tested against the derived distribution of bulge intrinsic ellipticities.Comment: 24 pages, 13 figures, accepted for publication in A&A, corrected proof

Optimization of an axial fan for air cooled condensers

We report on the low noise optimization of an axial fan specifically designed for the cooling of CSP power plants. The duty point presents an uncommon combination of a load coefficient of 0.11, a flow coefficient of 0.23 and a static efficiency ηstat &gt; 0.6. Calculated fan Reynolds number is equal to Re = 2.85 x 107. Here we present a process used to optimize and numerically verify the fan performance. The optimization of the blade was carried out with a Python code through a brute-force-search algorithm. Using this approach the chord and pitch distributions of the original blade are varied under geometrical constraints, generating a population of over 24000 different possible individuals. Each individual was then tested using an axisymmetric Python code. The software is based on a blade element axisymmetric principle whereby the rotor blade is divided into a number of streamlines. For each of these streamlines, relationships for velocity and pressure are derived from conservation laws for mass, tangential momentum and energy of incompressible flows. The final geometry was eventually chosen among the individuals with the maximum efficiency. The final design performance was then validated through with a CFD simulation. The simulation was carried out using a RANS approach, with the cubic k -  low Reynolds turbulence closure of Lien et al. The numerical simulation was able to verify the air performance of the fan and was used to derive blade-to-blade distributions of design parameters such as flow deviation, velocity components, specific work and diffusion factor of the optimized blade. All the computations were performed in OpenFoam, an open source C++- based CFD library. This work was carried out under MinWaterCSP project, funded by EU H2020 programme

Mountain landslides: Monitoring, modeling, and mitigation

This editorial paper summarizes the contents of the papers included in the Special Issue "Mountain Landslides: Monitoring, Modeling, and Mitigation". The Special Issue provides an overview of methodological papers, as well as some innovative research carried out in the field and in the lab. Even if most papers adopted an integrated approach, sections representing the three research issues outlined in the title can be drawn: the first deals with monitoring, the second focuses on modeling, and the third is related to mitigation. Regardless of the section, the papers included in this special issue put forward methodological and practical implications that, more than likely, can stimulate further research efforts and support the stakeholders to gain better knowledge of landslide hazards in mountain environments, with an aim to tackle the urgent issue of sustainable development in times of global change that can affect landslide occurrences in mountain chains of the world