Melting of PCM in a thermal energy storage unit: Numerical investigation and effect of nanoparticle enhancement

The present paper describes the analysis of the melting process in a single vertical shell‐and‐tube latent heat thermal energy storage (LHTES), unit and it is directed at understanding the thermal performance of the system. The study is realized using a computational fluid‐dynamic (CFD) model that takes into account of the phase‐change phenomenon by means of the enthalpy method. Fluid flow is fully resolved in the liquid phase‐change material (PCM) in order to elucidate the role of natural convection. The unsteady evolution of the melting front and the velocity and temperature fields is detailed. Temperature profiles are analyzed and compared with experimental data available in the literature. Other relevant quantities are also monitored, including energy stored and heat flux exchanged between PCM and HTF. The results demonstrate that natural convection within PCM and inlet HTF temperature significantly affects the phase‐change process. Thermal enhancement through the dispersion of highly conductive nanoparticles in the base PCM is considered in the second part of the paper. Thermal behavior of the LHTES unit charged with nano‐enhanced PCM is numerically analyzed and compared with the original system configuration. Due to increase of thermal conductivity, augmented thermal performance is observed: melting time is reduced of 15% when nano‐enhanced PCM with particle volume fraction of 4% is adopted. Similar improvements of the heat transfer rate are also detected. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

The main problem in dealing with energy-harvesting (EH) sensor nodes is represented by the scarcity and non-stationarity of powering, due to the nature of the renewable energy sources. In this work, the authors address the problem of task scheduling in processors located in sensor nodes powered by EH sources. Some interesting solutions have appeared in the literature in the recent past, as the lazy scheduling algorithm (LSA), which represents a performing mix of scheduling effectiveness and ease of implementation. With the aim of achieving a more efficient and conservative management of energy resources, a new improved LSA solution is here proposed. Indeed, the automatic ability of foreseeing at run-time the task energy starving (i.e. the impossibility of finalizing a task due to the lack of power) is integrated within the original LSA approach. Moreover, some modifications have been applied in order to reduce the LSA computational complexity and thus maximizing the amount of energy available for task execution. The resulting technique, namely energy-aware LSA, has then been tested in comparison with the original one, and a relevant performance improvement has been registered both in terms of number of executable tasks and in terms of required computational burden.     

Corrosion behaviour of sol–gel treated and painted AA2024 aluminium alloy

Design, development and scale-up of environmentally friendly coatings are very important in order to replace chromate based coatings for aluminium alloys. Barrier properties, paint adhesion and possibly self-healing ability are relevant aspects for replacement of chromate-based pre-treatments. Sol–gel materials are candidates for use in protective coating applications, as it is possible to form highly adherent and chemically inert oxide films on metal substrates.     

Changes of the main physical and technological properties of talc due to mechanical strain

A commercial talc was treated by planetary ball milling to evaluate the changes of the main physical and technological properties due to induced progressive mechanical stress.Firstly, a high orientation of talc platelets was obtained, secondly a progressive structural disorder of the talc and finally a re-aggregation of the particles during prolonged grinding was observed. Delamination during the initial and intermediate stages cannot be excluded.Mechanical grinding reduced the particles size and increased the specific surface area leading to enhanced absorption and cation exchange capacity during the initial and intermediate stages of grinding. The reduced lightness and brightness for prolonged grinding were attributed to the agglomeration of the particles. The mechanical treatment does not induce significant amorphization, thus preserving the main properties of talc even after prolonged grinding.     

Effects of solvent and alkaline earth metals on the heat-induced precipitation process of sodium caseinate

The precipitation temperatures of sodium caseinate in H₂O and D₂O in the presence of Mg²⁺, Ca²⁺, Sr²⁺ and Ba²⁺ were investigated through fluorescence, turbidity and conductivity experiments.     

On time-reversal and space-time harmonic processes for Markovian quantum channels

The time reversal of a completely-positive, nonequilibrium discrete-time quantum Markov evolution is derived in a general framework via a suitable adjointness relation. Space-time harmonic processes are then introduced for the forward and reverse-time transition mechanisms, and their role in the study of quantum dynamics is illustrated by discussing (operator and scalar) relative entropy dynamics.     

Riparian Vegetation Mapping for Hydraulic Roughness Estimation Using Very High Resolution Remote Sensing Data Fusion

For detailed hydraulic modeling, accurate spatial information of riparian vegetation patterns needs to be derived in automatic fashion. We propose a supervised classification for heterogeneous riparian corridors with a low number of spectrally separate classes using data fusion of a Quickbird image and LIDAR data. The approach considers nine land cover classes including three woody riparian species, brush, cultivated areas, grassland, urban infrastructures, bare soil and water. The classical “stacked vector” approach is adopted for data fusion, while the nonparametric weighted feature-extraction method and the pixel-oriented maximum likelihood algorithm are used for feature-reduction and classification purposes, respectively. We test the approach over a 14-km stretch of the Sieve River (Tuscany Region, Italy). A one-dimensional river modeling is applied over the study reach comparing the results of a classification-derived hydraulic roughness map and a traditional ground-based approach. Despite the complex study reach, the classification method produced encouraging accuracies (OKS = 0.77) and represents a useful tool to delineate application domains of flow resistance models suited to different hydrodynamic patterns (e.g., stiff/flexible vegetation). Hydraulic modeling results showed that the remotely derived floodplain roughness parameterization captures the equivalent Manning coefficient over 20 test cross sections with uncertainty distributions described by low mean and standard deviation values.