Showing papers by "National Technical University of Athens published in 2009"

A review of grid code technical requirements for wind farms

Abstract: This paper provides an overview of grid code technical requirements regarding the connection of large wind farms to the electric power systems. The grid codes examined are generally compiled by transmission system operators (TSOs) of countries or regions with high wind penetration and therefore incorporate the accumulated experience after several years of system operation at significant wind penetration levels. The paper focuses on the most important technical requirements for wind farms, included in most grid codes, such as active and reactive power regulation, voltage and frequency operating limits and wind farm behaviour during grid disturbances. The paper also includes a review of modern wind turbine technologies, regarding their capability of satisfying the requirements set by the codes, demonstrating that recent developments in wind turbine technology provide wind farms with stability and regulation capabilities directly comparable to those of conventional generating plants.

Modelling and measuring flow and wind turbine wakes in large wind farms offshore

Abstract: Average power losses due to wind turbine wakes are of the order of 10 to 20% of total power output in large offshore wind farms. Accurately quantifying power losses due to wakes is, therefore, an important part of overall wind farm economics. The focus of this research is to compare different types of models from computational fluid dynamics (CFD) to wind farm models in terms of how accurately they represent wake losses when compared with measurements from offshore wind farms. The ultimate objective is to improve modelling of flow for large wind farms in order to optimize wind farm layouts to reduce power losses due to wakes and loads. The research presented is part of the EC-funded UpWind project, which aims to radically improve wind turbine and wind farm models in order to continue to improve the costs of wind energy. Reducing wake losses, or even reduce uncertainties in predicting power losses from wakes, contributes to the overall goal of reduced costs. Here, we assess the state of the art in wake and flow modelling for offshore wind farms, the focus so far has been cases at the Horns Rev wind farm, which indicate that wind farm models require modification to reduce under-prediction of wake losses while CFD models typically over-predict wake losses. Further investigation is underway to determine the causes of these discrepancies. Copyright © 2009 John Wiley & Sons, Ltd.

Assessment of Hydrological Drought Revisited

Abstract: A variety of indices for characterising hydrological drought have been devised which, in general, are data demanding and computationally intensive. On the contrary, for meteorological droughts very simple and effective indices such as the Standardised Precipitation Index (SPI) have been used. A methodology for characterising the severity of hydrological droughts is proposed which uses an index analogous to SPI, the Streamflow Drought Index (SDI). Cumulative streamflow is used for overlapping periods of 3, 6, 9 and 12 months within each hydrological year. Drought states are defined which form a non-stationary Markov chain. Prediction of hydrological drought based on precipitation is also investigated. The methodology is validated using reliable data from the Evinos river basin (Greece). It can be easily applied within a Drought Watch System in river basins with significant storage works and can cope with the lack of streamflow data.

DIANA-microT web server: elucidating microRNA functions through target prediction

Abstract: Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

Logistics issues of biomass: The storage problem and the multi-biomass supply chain

Abstract: Biomass is a renewable energy source with increasing importance. The larger fraction of cost in biomass energy generation originates from the logistics operations. A major issue concerning biomass logistics is its storage, especially when it is characterized by seasonal availability. The biomass energy exploitation literature has rarely investigated the issue of biomass storage. Rather, researchers usually choose arbitrarily the lowest cost storage method available, ignoring the effects this choice may have on the total system efficiency. In this work, the three most frequently used biomass storage methods are analyzed and are applied to a case study to come up with tangible comparative results. Furthermore, the issue of combining multiple biomass supply chains, aiming at reducing the storage space requirements, is introduced. An application of this innovative concept is also performed for the case study examined. The most important results of the case study are that the lowest cost storage method indeed constitutes the system-wide most efficient solution, and that the multi-biomass approach is more advantageous when combined with relatively expensive storage methods. However, low cost biomass storage methods bear increased health, safety and technological risks that should always be taken into account.

The behavior of self-compacting concrete containing micro-encapsulated Phase Change Materials

Abstract: In order to come to a sustainable built environment the construction industry requires new energy saving concepts. One concept is to use Phase Change Materials (PCM), which have the ability to absorb and to release thermal energy at a specific temperature. This paper presents a set of experiments using different amounts of PCM in self-compacting concrete mixes. The study focuses on the direct mixing of micro-encapsulated PCM with concrete and its influence on the material properties. Therefore, the fresh concrete properties and the hardened properties are investigated. The hardened properties comprise strength tests and a thorough assessment of the thermal properties. It will be shown that increasing PCM amounts lead to lower thermal conductivity and increased heat capacity, which both significantly improve the thermal performance of concrete and therefore save energy. On the other hand a significant loss in strength and micro-structural analysis both indicate that a large part of the capsules is destroyed during the mixing process and releases its paraffin wax filling into the surrounding matrix. However, the compressive strength of our specimens still satisfies the demands of most structural applications.

Accurate microRNA target prediction correlates with protein repression levels

Abstract: MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

Dropout prediction in e-learning courses through the combination of machine learning techniques

Abstract: In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to accurately classify some e-learning students, whereas another may succeed, three decision schemes, which combine in different ways the results of the three machine learning techniques, were also tested. The method was examined in terms of overall accuracy, sensitivity and precision and its results were found to be significantly better than those reported in relevant literature.

A critical assessment of pedestrian behaviour models

Abstract: This paper concerns a review and critical assessment of the existing research on pedestrian behaviour in urban areas, focusing on two separate yet complementary aspects: route choice and crossing behaviour. First, an exhaustive review of the existing route choice models for pedestrians is presented. It is shown that the existing models are mainly more stochastic and more macroscopic than required and seldom incorporate the interactions between pedestrians and traffic. Second, the existing models on pedestrians crossing behaviour are presented and assessed. It is shown that, although their approach is usually detailed, deterministic and traffic-oriented, they are mainly devoted to a local level behaviour and focus on only one type of all the potential determinants. Most importantly, these two complementary and possibly interdependent aspects of pedestrian behaviour are always examined separately. The results of this review reveal a lack of an overall and detailed consideration of pedestrian behaviour along an entire trip in urban areas. Moreover, the need for an integrated approach based on flexibility, disaggregation and more determinism is identified. Accordingly, a set of modelling techniques are discussed as a general framework for further research in the field.

Incremental dynamic analysis for estimating seismic performance sensitivity and uncertainty

Abstract: SUMMARY Incremental Dynamic Analysis (IDA) is presented as a powerful tool to evaluate the variability in the seismic demand and capacity of non-deterministic structural models, building upon existing methodologies of Monte Carlo simulation and approximate moment-estimation. A nine-story steel moment-resisting frame is used as a testbed, employing parameterized moment-rotation relationships with non-deterministic quadrilinear backbones for the beam plastic-hinges. The uncertain properties of the backbones include the yield moment, the post-yield hardening ratio, the end-of-hardening rotation, the slope of the descending branch, the residual moment capacity and the ultimate rotation reached. IDA is employed to accurately assess the seismic performance of the model for any combination of the parameters by performing multiple nonlinear timehistory analyses for a suite of ground motion records. Sensitivity analyses on both the IDA and the static pushover level reveal the yield moment and the two rotational-ductility parameters to be the most in∞uential for the frame behavior. To propagate the parametric uncertainty to the actual seismic performance we employ a) Monte Carlo simulation with latin hypercube sampling, b) point-estimate and c) flrst-order second-moment techniques, thus ofiering competing methods that represent difierent compromises between speed and accuracy. The flnal results provide flrm ground for challenging current assumptions in seismic guidelines on using a median-parameter model to estimate the median seismic performance and employing the well-known square-root-sum-of-squares rule to combine aleatory randomness and epistemic uncertainty. Copyright c ∞ 2009 John Wiley & Sons, Ltd.

Polymerization in sodium silicate solutions: a fundamental process in geopolymerization technology

Abstract: Geopolymerization is an innovative technology that can transform several solid aluminosilicate materials into useful products called geopolymers or inorganic polymers. Although the geopolymerization mechanism is not well understood, the most proposed mechanism includes four parallel stages: (a) dissolution of solid aluminosilicate materials in alkaline sodium silicate solution, (b) oligomerization of Si and/or Si–Al in aqueous phase, (c) polymerization of the oligomeric species, and (d) bonding of undissolved solid particles in the polymer. It is obvious that polymerization in sodium silicate solutions comprises a fundamental process in geopolymerization technology. Therefore, this article aims at studying experimentally the polymerization stage in synthetic pure sodium silicate solutions. The structure of sodium silicate gels as a function of the SiO2/Na2O molar ratio is examined and their hardness as well as hydrolytic stability are determined. In addition, the effect of aluminum incorporation in the hydrolytic stability of these gels is also examined. Finally, the structure of sodium silicate and aluminosilicate gels is correlated to the measured properties drawing very useful conclusions that could be applied on geopolymerization technology.

Comparative Study of Active Thermography Techniques for the Nondestructive Evaluation of Honeycomb Structures

Abstract: In this article, the theoretical and experimental aspects of three active thermography approaches: pulsed thermography (PT), lock-in thermography (LT), and vibrothermography (VT), are discussed in relation to the nondestructive evaluation (NDE) of honeycomb sandwich structures. For this purpose, two standard specimens with simulated defects (delaminations, core unbonds, excessive adhesive, and crushed core) were tested, and results were processed, examined, and compared. As will be pointed out, the similarities and differences between these active approaches allow conclusions to be made about the most suitable approach for a particular application. In addition, results from NDE inspection by X-rays and c-scan ultrasounds are provided and discussed for reference.

Transit Route Network Design Problem: Review

Abstract: Efficient design of public transportation networks has attracted much interest in the transport literature and practice, with many models and approaches for formulating the associated transit route network design problem (TRNDP) having been developed. The present paper systematically presents and reviews research on the TRNDP based on the three distinctive parts of the TRNDP setup: design objectives, operating environment parameters and solution approach.

Effect of dietary fibre enrichment on selected properties of gluten-free bread.

Abstract: The enrichment of gluten-free baked products with dietary fibre seems to be necessary since it has been reported that coeliac patients have generally a low intake of fibre due to their gluten-free diet. In the present study different cereal fibres (wheat, maize, oat and barley) were added at 3, 6 and 9 g/100 g level into a gluten-free bread formulation based on corn starch, rice flour and hydroxypropyl methyl cellulose (HPMC). Doughs were evaluated based on consistency, viscosity and thermal properties. Results showed that maize and oat fibre can be added to gluten-free bread with positive impact on bread nutritional and sensory properties. All breads with 9 g/100 g fibre increased the fibre content of control by 218%, but they were rated lower than those with 3 and 6 g/100 g fibre due to their powdery taste. The formulation containing barley fibre produced loaves that had more intense color and volume comparable to the control. During storage of breads a reduction in crumb moisture content and an increase in firmness were observed. The micrographs of the crumb showed the continuous matrix between starch and maize and/or oat fibre obtaining a more aerated structure.

An optimization model for multi-biomass tri-generation energy supply

Abstract: In this paper, a decision support system (DSS) for multi-biomass energy conversion applications is presented. The system in question aims at supporting an investor by thoroughly assessing an investment in locally existing multi-biomass exploitation for tri-generation applications (electricity, heating and cooling), in a given area. The approach followed combines use of holistic modelling of the system, including the multi-biomass supply chain, the energy conversion facility and the district heating and cooling network, with optimization of the major investment-related variables to maximize the financial yield of the investment. The consideration of multi-biomass supply chain presents significant potential for cost reduction, by allowing spreading of capital costs and reducing warehousing requirements, especially when seasonal biomass types are concerned. The investment variables concern the location of the bioenergy exploitation facility and its sizing, as well as the types of biomass to be procured, the respective quantities and the maximum collection distance for each type. A hybrid optimization method is employed to overcome the inherent limitations of every single method. The system is demand-driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of an investor to assess and optimize in financial terms an investment aiming at covering real energy demand. Optimization is performed taking into account various technical, regulatory, social and logical constraints. The model characteristics and advantages are highlighted through a case study applied to a municipality of Thessaly, Greece.

Human factors and qualitative pedagogical evaluation of a mobile augmented reality system for science education used by learners with physical disabilities

Abstract: Technology-enhanced learning, employing novel forms of content representation and education service delivery by enhancing the visual perception of the real environment of the user, is favoured by proponents of educational inclusion for learners with physical disabilities. Such an augmented reality computer-mediated learning system has been developed as part of an EU funded research project, namely the CONNECT project. The CONNECT project brings together schools and science centres, and produces novel information and communication technologies based on augmented reality (AR) and web-based streaming and communication, in order to support learning in a variety of settings. The CONNECT AR interactive learning environment can assist users to better contextualize and reinforce their learning in school and in other settings where people learn (i.e. science centres and home). The CONNECT concept and associated technologies encourage users to visit science centres and perform experiments that are not possible in school. They can also build on these experiences back at school and at home with visual augmentations that they are communicated through web-based streaming technology. This paper particularly focuses on a user-centred evaluation approach of human factors and pedagogical aspects of the CONNECT system, as applied to a special needs user group. The main focus of the paper is on highlighting the human factors issues and challenges, in terms of wearability and technology acceptance, while elaborating on some qualitative aspects of the pedagogical effectiveness of the instructional medium that AR technology offers for this group of learners.