Showing papers by "National Technical University of Athens published in 2008"

Making microgrids work

Abstract: Distributed energy resources including distributed generation and distributed storage are sources of energy located near local loads and can provide a variety of benefits including improved reliability if they are properly operated in the electrical distribution system. Microgrids are systems that have at least one distributed energy resource and associated loads and can form intentional islands in the electrical distribution systems. This paper gives an overview of the microgrid operation. Microgrid testing experiences from different counties was also provided.

Systematic lidar observations of Saharan dust over Europe in the frame of EARLINET (2000-2002)

Abstract: [1] More than 130 observation days of the horizontal and vertical extent of Saharan dust intrusions over Europe during the period May 2000 to December 2002 were studied by means of a coordinated lidar network in the frame of the European Aerosol Research Lidar Network (EARLINET). The number of dust events was greatest in late spring, summer, and early autumn periods, mainly in southern (S) and southeastern (SE) Europe. Multiple aerosol dust layers of variable thickness (300–7500 m) were observed. The center of mass of these layers was located in altitudes between 850 and 8000 m. However, the mean thickness of the dust layer typically stayed around 1500–3400 m and the corresponding mean center of mass ranged from 2500 to 6000 m. In exceptional cases, dust aerosols reached northwestern (NW), northern (N), or northeastern (NE) Europe, penetrating the geographical area located between 4°W–28°E (longitude) and 38°N–58°N (latitude). Mean aerosol optical depths (AOD), extinction-to-backscatter ratios (lidar ratios, LR), and linear depolarization ratios of desert aerosols ranged from 0.1 to 0.25 at the wavelength of 355 or 351 nm, 30 to 80 sr at 355 or 351 nm, and 10 to 25% at 532 nm, respectively, within the lofted dust plumes. In these plumes typical Saharan dust backscatter coefficients ranged from 0.5 to 2 Mm−1sr−1. Southern European stations presented higher variability of the LR values and the backscatter-related Angstrom exponent values (BRAE) (LR: 20–100 sr; BRAE: −0.5 to 3) than northern ones (LR: 30–80 sr; BRAE: −0.5 to 1).

SANISAND : Simple anisotropic sand plasticity model

Abstract: SANISAND is the name used for a family of simple anisotropic sand constitutive models developed over the past few years within the framework of critical state soil mechanics and bounding surface plasticity. The existing SANISAND models use a narrow open cone-type yield surface with apex at the origin obeying rotational hardening, which implies that only changes of the stress ratio can cause plastic deformations, while constant stress-ratio loading induces only elastic response. In order to circumvent this limitation, the present member of the SANISAND family introduces a modified eight-curve equation as the analytical description of a narrow but closed cone-type yield surface that obeys rotational and isotropic hardening. This modification enables the prediction of plastic strains during any type of constant stress-ratio loading, a feature lacking from the previous SANISAND models, without losing their well-established predictive capability for all other loading conditions including the cyclic. In the process the plausible assumption is made that the plastic strain rate decomposes in two parts, one due to the change of stress ratio and a second due to loading under constant stress ratio, with isotropic hardening depending on the volumetric component of the latter part only. The model formulation is presented firstly in the triaxial stress space and subsequently its multiaxial generalization is developed following systematically the steps of the triaxial one. A detailed calibration procedure for the model constants is presented, while successful simulation of both drained and undrained behavior of sands under constant and variable stress-ratio loadings at various densities and confining pressures is obtained by the model.

Monte Carlo studies of supersymmetric matrix quantum mechanics with sixteen supercharges at finite temperature.

Abstract: We present the first Monte Carlo results for supersymmetric matrix quantum mechanics with 16 supercharges at finite temperature. The recently proposed nonlattice simulation enables us to include the effects of fermionic matrices in a transparent and reliable manner. The internal energy nicely interpolates the weak coupling behavior obtained by the high temperature expansion, and the strong coupling behavior predicted from the dual black-hole geometry. The Polyakov line asymptotes at low temperature to a characteristic behavior for a deconfined theory, suggesting the absence of a phase transition. These results provide highly nontrivial evidence for the gauge-gravity duality.

Emotion Recognition through Multiple Modalities: Face, Body Gesture, Speech

Abstract: In this paper we present a multimodal approach for the recognition of eight emotions. Our approach integrates information from facial expressions, body movement and gestures and speech. We trained and tested a model with a Bayesian classifier, using a multimodal corpus with eight emotions and ten subjects. Firstly, individual classifiers were trained for each modality. Next, data were fused at the feature level and the decision level. Fusing the multimodal data resulted in a large increase in the recognition rates in comparison with the unimodal systems: the multimodal approach gave an improvement of more than 10% when compared to the most successful unimodal system. Further, the fusion performed at the feature level provided better results than the one performed at the decision level.

Degree Theory for Operators of Monotone Type and Nonlinear Elliptic Equations With Inequality Constraints

Abstract: Introduction Mathematical background Degree theoretic results Variational-hemivariational inequalities Hemivariational inequalities with an asymmetric subdifferential Bibliography.

On the credibility of climate predictions

Abstract: Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.

CO2 Emissions Statistics for the World Commercial Fleet

Abstract: The purpose of this paper is to present an analysis of carbon dioxide (CO2) emissions of the world commercial fleet. The analysis is based on the Lloyds-Fairplay world ship database for 2007 and produces various emissions statistics of the following major ship types: bulk carriers, crude oil tankers, container vessels, product/chemical carriers, LNG carriers, LPG carriers, reefer vessels, Ro-Ro vessels and general cargo ships. A separate analysis is carried out for small vessels under 400 GRT and for passenger vessels. The main outputs from this analysis for each ship type-size bracket are the emitted grams of CO2 per tonne-km and an estimate of the total CO2 produced in a year. The methodology for estimating these statistics is described, and a comparison with other studies is made.

Supercritical Fluid Parameters in Organic Rankine Cycle Applications

Abstract: Nowadays, the use of Organic Rankine Cycle (ORC) in decentralised applications is linked with the fact that this process allows to use low temperature heat sources and offers an advantageous efficiency in small-scale applications. Many state of the art applications like geothermal and biomass fired power plants as well as new applications like solar desalination with reverse osmosis, waste heat recovery from biogas digestion plants or micro-Combined Heat and Power (micro-CHP) systems can successfully use the ORC process. The investigation of supercritical parameters in ORC applications seems to bring promising results in decentralised energy production. This paper presents the results from the simulation of the ORC process in normal and supercritical fluid parameters and discusses the efficiency variation in various applications.

Study of the functionality of selected hydrocolloids and their blends with κ-carrageenan on storage quality of vanilla ice cream

Abstract: In the present paper, the functionality of hydrocolloids related to the rheological, physical and sensory characteristics of ice cream mixes and frozen ice cream was studied. Carboxylmethylcellulose, guar gum, sodium alginate and xanthan gum were used as primary stabilizing agents, whereas κ-carrageenan as secondary. The hydrocolloid concentrations were 0.1 and 0.2% and the primary to secondary ratio was 9:1. The ice cream samples were stored under quiescent frozen conditions. Samples were taken after 4, 8 and 16 weeks of storage and examined for the functionality of the stabilizing systems. The addition of hydrocolloids significantly reinforced the shear thinning behavior, particularly in the case of sodium alginate, xanthan gum, and κ-carrageenan which was attributed to gelation phenomena. Sodium alginate attained the better stabilizing effect improving textural quality and acceptance of ice creams even after 16 weeks of storage, whereas the presence of κ-carrageenan found to be a crucial factor for the cryoprotection. Xanthan gum was also evaluated as an effective stabilizing agent, indicating that gelling hydrocolloids may remarkably amend ice cream shelf life. Moreover, principal components and cluster analysis of instrumental and sensory data furnished important information for the correlation of objective and sensory properties and discrimination of stabilizing systems based on quality criteria.

Support Vector Machine Classification for Object-Based Image Analysis

Abstract: The Support Vector Machine is a theoretically superior machine learning methodology with great results in pattern recognition. Especially for supervised classification of high-dimensional datasets and has been found competitive with the best machine learning algorithms. In the past, SVMs were tested and evaluated only as pixel-based image classifiers. During recent years, advances in Remote Sensing occurred in the field of Object-Based Image Analysis (OBIA) with combination of low level and high level computer vision techniques. Moving from pixel-based techniques towards object-based representation, the dimensions of remote sensing imagery feature space increases significantly. This results to increased complexity of the classification process, and causes problems to traditional classification schemes. The objective of this study was to evaluate SVMs for their effectiveness and prospects for object-based image analysis as a modern computational intelligence method. Here, an SVM approach for multi-class classification was followed, based on primitive image objects provided by a multi-resolution segmentation algorithm. Then, a feature selection step took place in order to provide the features for classification which involved spectral, texture and shape information. After the feature selection step, a module that integrated an SVM classifier and the segmentation algorithm was developed in C++. For training the SVM, sample image objects derived from the segmentation procedure were used. The proposed classification procedure followed, resulting in the final object classification. The classification results were compared to the Nearest Neighbor object-based classifier results, and were found satisfactory. The SVM methodology seems very promising for Object Based Image Analysis and future work will focus on integrating SVM classifiers with rule-based classifiers.