Showing papers by "Grenoble Institute of Technology published in 2011"

Optimal Power Flow Management for Grid Connected PV Systems With Batteries

Abstract: This paper presents an optimal power management mechanism for grid connected photovoltaic (PV) systems with storage. The objective is to help intensive penetration of PV production into the grid by proposing peak shaving service at the lowest cost. The structure of a power supervisor based on an optimal predictive power scheduling algorithm is proposed. Optimization is performed using Dynamic Programming and is compared with a simple ruled-based management. The particularity of this study remains first in the consideration of batteries ageing into the optimization process and second in the “day-ahead” approach of power management. Simulations and real conditions application are carried out over one exemplary day. In simulation, it points out that peak shaving is realized with the minimal cost, but especially that power fluctuations on the grid are reduced which matches with the initial objective of helping PV penetration into the grid. In real conditions, efficiency of the predictive schedule depends on accuracy of the forecasts, which leads to future works about optimal reactive power management.

Cellulose-Based Bio- and Nanocomposites: A Review

Abstract: Cellulose macro- and nanofibers have gained increasing attention due to the high strength and stiffness, biodegradability and renewability, and their production and application in development of composites. Application of cellulose nanofibers for the development of composites is a relatively new research area. Cellulose macro- and nanofibers can be used as reinforcement in composite materials because of enhanced mechanical, thermal, and biodegradation properties of composites. Cellulose fibers are hydrophilic in nature, so it becomes necessary to increase their surface roughness for the development of composites with enhanced properties. In the present paper, we have reviewed the surface modification of cellulose fibers by various methods. Processing methods, properties, and various applications of nanocellulose and cellulosic composites are also discussed in this paper.

First-principles investigation of the very large perpendicular magnetic anisotropy at Fe|MgO and Co|MgO interfaces

Abstract: The perpendicular magnetic anisotropy (PMA) arising at the interface between ferromagnetic transition metals and metallic oxides was investigated via first-principles calculations. In this work very large values of PMA, up to 3 erg/cm${}^{2}$, at Fe$|$MgO interfaces are reported, in agreement with recent experiments. The origin of PMA is attributed to overlap between O-${p}_{z}$ and transition metal ${d}_{{z}^{2}}$ orbitals hybridized with ${d}_{xz(yz)}$ orbitals with stronger spin-orbit coupling-induced splitting around the Fermi level for perpendicular magnetization orientation. Furthermore, it is shown that the PMA value weakens in the case of over- or underoxidation due to the fact that oxygen ${p}_{z}$ and transition metal ${d}_{{z}^{2}}$ orbital overlap is strongly affected by disorder, in agreement with experimental observations in magnetic tunnel junctions.

Classification of Hyperspectral Images by Using Extended Morphological Attribute Profiles and Independent Component Analysis

Abstract: In this letter, a technique based on independent component analysis (ICA) and extended morphological attribute profiles (EAPs) is presented for the classification of hyperspectral images. The ICA maps the data into a subspace in which the components are as independent as possible. APs, which are extracted by using several attributes, are applied to each image associated with an extracted independent component, leading to a set of extended EAPs. Two approaches are presented for including the computed profiles in the analysis. The features extracted by the morphological processing are then classified with an SVM. The experiments carried out on two hyperspectral images proved the effectiveness of the proposed technique.

Hyperspectral Image Classification With Independent Component Discriminant Analysis

Abstract: In this paper, the use of Independent Component (IC) Discriminant Analysis (ICDA) for remote sensing classification is proposed. ICDA is a nonparametric method for discriminant analysis based on the application of a Bayesian classification rule on a signal composed by ICs. The method uses IC Analysis (ICA) to choose a transform matrix so that the transformed components are as independent as possible. When the data are projected in an independent space, the estimates of their multivariate density function can be computed in a much easier way as the product of univariate densities. A nonparametric kernel density estimator is used to compute the density functions of each IC. Finally, the Bayes rule is applied for the classification assignment. In this paper, we investigate the possibility of using ICDA for the classification of hyperspectral images. We study the influence of the algorithm used to enforce independence and of the number of IC retained for the classification, proposing an effective method to estimate the most suitable number. The proposed method is applied to several hyperspectral images, in order to test different data set conditions (urban/agricultural area, size of the training set, and type of sensor). Obtained results are compared with one of the most commonly used classifier of hyperspectral images (support vector machines) and show the comparative effectiveness of the proposed method in terms of accuracy.

Chipless RFID Tag Using Hybrid Coding Technique

Abstract: Increasing the coding capacity of chipless RFID tags is a key factor while considering the development of miniaturized tags. A novel hybrid coding technique by combining phase deviation and frequency position encoding is proposed here. A coding capacity of 22.9 bits is obtained simply with five resonators within a reduced dimension of 2 cm × 4 cm. The proposed tag is based on 5 `C' like metallic strip resonators having resonance frequency within the band of 2.5 GHz to 7.5 GHz. The tag is potentially low-cost since only one conductive layer is needed for the fabrication. Different tag configurations are designed and validated with measurement results in bi-static configuration. A good agreement between measurement and simulation validates the theoretical predictions.

Modeling the mechanics of amorphous solids at different length scale and time scale

Abstract: We review the recent literature on the simulation of the structure and deformation of amorphous solids, including oxide and metallic glasses. We consider simulations at different length scale and time scale. At the nanometer scale, we review studies based on atomistic simulations, with a particular emphasis on the role of the potential energy landscape and of the temperature. At the micrometer scale, we present the different mesoscopic models of amorphous plasticity and show the relation between shear banding and the type of disorder and correlations (e.g. elastic) included in the models. At the macroscopic range, we review the different constitutive laws used in finite-element simulations. We end with a critical discussion on the opportunities and challenges offered by multiscale modeling and information transfer between scales to study amorphous plasticity.

Production of pions, kaons and protons in pp collisions at root s=900 GeV with ALICE at the LHC

Abstract: The production of π+, π−, K+, K−, p, and \(\overline{\mathrm{p}}\) at mid-rapidity has been measured in proton-proton collisions at \(\sqrt{s} = 900~\mathrm{GeV}\) with the ALICE detector. Particle identification is performed using the specific energy loss in the inner tracking silicon detector and the time projection chamber. In addition, time-of-flight information is used to identify hadrons at higher momenta. Finally, the distinctive kink topology of the weak decay of charged kaons is used for an alternative measurement of the kaon transverse momentum (pt) spectra. Since these various particle identification tools give the best separation capabilities over different momentum ranges, the results are combined to extract spectra from pt=100 MeV/c to 2.5 GeV/c. The measured spectra are further compared with QCD-inspired models which yield a poor description. The total yields and the mean pt are compared with previous measurements, and the trends as a function of collision energy are discussed.

Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan

Abstract: . A major proportion of flow in the Indus River is contributed by its snow- and glacier-fed river catchments situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere dynamics in this area for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover changes in the Hunza River basin (the snow- and glacier-fed sub-catchment of the Indus River). A database of daily flows for the Hunza River at Dainyor Bridge over a period of 40 yr and climate data (precipitation and temperature) for 10 yr from three meteorological stations within the catchment was made available to investigate the hydrological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data during the last decade (2000–2009) suggest a rather slight expansion of cryosphere in the area in contrast to most of the regions in the world where glaciers are melting rapidly. This increase in snow cover may be the result of an increase in winter precipitation caused by westerly circulation. The impact of global warming is not effective because a large part of the basin area lies under high altitudes where the temperature remains negative throughout most of the year.

Spectral Unmixing for the Classification of Hyperspectral Images at a Finer Spatial Resolution

Abstract: The problem of classification of hyperspectral images containing mixed pixels is addressed. Hyperspectral imaging is a continuously growing area of remote sensing applications. The wide spectral range of such imagery, providing a very high spectral resolution, allows to detect and classify surfaces and chemical elements of the observed image. The main problem of hyperspectral data is the (relatively) low spatial resolution, which can vary from a few to tens of meters. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. For classification, the major problem caused by low spatial resolution are the mixed pixels, i.e., parts of the image where more than one land cover map lie in the same pixel. In this paper, we propose a method to address the problem of mixed pixels and to obtain a finer spatial resolution of the land cover classification maps. The method exploits the advantages of both soft classification techniques and spectral unmixing algorithms, in order to determine the fractional abundances of the classes at a sub-pixel scale. Spatial regularization by simulated annealing is finally performed to spatially locate the obtained classes. Experiments carried out on synthetic real data sets show excellent results both from a qualitative and quantitative point of view.

High spatial resolution semi-automatic crystallite orientation and phase mapping of nanocrystals in transmission electron microscopes

Abstract: A semi-automatic technique for the mapping of nanocrystal phases and orientations in a transmission electron microscope (TEM) is described. It is based primarily on the projected reciprocal lattice geometry, but also utilizes the intensity of reflections that are extracted from precession-enhanced electron diffraction spot patterns of polycrystalline materials and multi-material composites. At the core of the method, experimental (precession-enhanced) electron diffraction spot patterns are cross correlated with pre-calculated templates for a set of model structures. The required hardware facilitates a scanning-precession movement of the primary electron beam on the polycrystalline and/or multi-material sample and can be interfaced to any newer or older mid-voltage TEM. The software that goes with this hardware is so flexible in its intake of experimental data that it can also create crystallite orientation and phase maps of nanocrystals from the amplitude part of Fourier transforms of high resolution TEM images. Experimentally obtained crystallite orientation and phase maps are shown for a clausthalite nanocrystal powder sample, polycrystalline aluminum and copper films, fine-grained palladium films, as well as MnAs crystallites that are partly embedded in a GaAs wafer. Comprehensive open-access and commercial crystallographic databases that may provide reference data in support of the nanocrystal phase identification process of the software are briefly mentioned. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Runtime enforcement monitors: composition, synthesis, and enforcement abilities

Abstract: Runtime enforcement is a powerful technique to ensure that a program will respect a given set of properties. We extend previous work on this topic in several directions. Firstly, we propose a generic notion of enforcement monitors based on a memory device and finite sets of control states and enforcement operations. Moreover, we specify their enforcement abilities w.r.t. the general Safety-Progress classification of properties. Furthermore, we propose a systematic technique to produce a monitor from the automaton recognizing a given safety, guarantee, obligation or response property. Finally, we show that this notion of enforcement monitors is more amenable to implementation and encompasses previous runtime enforcement mechanisms.

Mechanical properties of natural rubber nanocomposites reinforced with cellulosic nanoparticles obtained from combined mechanical shearing, and enzymatic and acid hydrolysis of sisal fibers

Abstract: In a previous work (Siqueira et al. 2010b) the preparation of cellulosic nanoparticles from sisal fibers using different processing routes, viz. a combination of mechanical shearing, acid and enzymatic hydrolysis was reported. It was shown that the pre-enzymatic hydrolysis treatment of bleached sisal pulp helps the preparation of well individualized rod-like nanocrystals. An amorphous polymer (natural rubber—NR) was chosen as model matrix to investigate the effect of these nanoparticles on the thermo-mechanical properties of nanocomposites. Both tensile tests and dynamic mechanical analyses showed improved stiffness for all nanocomposites. The enzymatic treatment allowed production of a huge range of cellulosic nanoparticles which provided completely different mechanical properties to NR matrix.

Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models

Abstract: In this paper, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter. Then, a detailed analysis is carried out to evaluate the potential of this new multivariate distribution. It is implemented in a hierarchical maximum likelihood segmentation algorithm. The segmentation results are shown on both synthetic and high-resolution PolSAR data at the X- and L-bands. Finally, some methods are examined to determine automatically the “optimal” number of segments in the final partition.

Two-scale modeling of granular materials: a DEM-FEM approach

Abstract: The presented study considers a two-scale numerical scheme for the description of the behavior of granular materials. At the small-scale level, the granular structure consists of 2D round rigid grains, modeled by the Discrete Element Method (DEM). At the macroscopic level, we consider a numerical solution obtained with the Finite Element Method (FEM). The link between scales is made using a computational homogenization method, in which the average REV stress response of the granular micro structure, together with the tangent moduli, are obtained in each macroscopic Gauss point of the FEM mesh as the result of the macroscopic deformation history imposed to the REV. In this way, the numerical constitutive law and the corresponding tangent matrix are obtained directly from the discrete behavior of the microstructure. We discuss the principle of the computational homogenization applied to this association of FEM with DEM and we present examples of the two-scale computations, like drained and undrained biaxial tests.