Analysis and validation of CFD wind farm models in complex terrain. Effects induced by topography and wind turbines

Wind farms have been extensively simulated through engineering models for the estimation of wind speed and power deficits inside wind farms. These models were designed initially for a few wind turbines located in flat terrain. Other models based on the parabolic approximation of Navier Stokes equations were developed, making more realistic and feasible the operational resolution of big wind farms in flat terrain and offshore sites. These models have demonstrated to be accurate enough when solving wake effects for this type of environments. Nevertheless, few analyses exist on how complex terrain can affect the behaviour of wind farm wake flow. Recent numerical studies have demonstrated that topographical wakes induce a significant effect on wind turbines wakes, compared to that on flat terrain. This circumstance has recommended the development of elliptic CFD models which allow global simulation of wind turbine wakes in complex terrain. An accurate simplification for the analysis of wind turbine wakes is the actuator disk technique. Coupling this technique with CFD wind models enables the estimation of wind farm wakes preserving the extraction of axial momentum present inside wind farms. This paper describes the analysis and validation of the elliptical wake model CFDWake 1.0 against experimental data from an operating wind farm located in complex terrain. The analysis also reports whether it is possible or not to superimpose linearly the effect of terrain and wind turbine wakes. It also represents one of the first attempts to observe the performance of engineering models compares in large complex terrain wind farms.

Microstructural segmentation of 3D images of alsphalt specimen using Matlab engine

En este proyecto se ha desarrollado un código de MATLAB para el procesamiento de imágenes tomográficas 3D, de muestras de asfalto de carreteras en Polonia. Estas imágenes en 3D han sido tomadas por un equipo de investigación de la Universidad Tecnológica de Lodz (LUT). El objetivo de este proyecto es crear una herramienta que se pueda utilizar para estudiar las diferentes muestras de asfalto 3D y pueda servir para estudiar las pruebas de estrés que experimentan las muestras en el laboratorio. Con el objetivo final de encontrar soluciones a la degradación sufrida en las carreteras de Polonia, debido a diferentes causas, como son las condiciones meteorológicas. La degradación de las carreteras es un tema que se ha investigado desde hace muchos años, debido a la fuerte degradación causada por diferentes factores como son climáticos, la falta de mantenimiento o el tráfico excesivo en algunos casos. Es en Polonia, donde estos tres factores hacen que la composición de muchas carreteras se degrade rápidamente, sobre todo debido a las condiciones meteorológicas sufridas a lo largo del año, con temperaturas que van desde 30° C en verano a -20° C en invierno. Esto hace que la composición de las carreteras sufra mucho y el asfalto se levante, lo que aumenta los costos de mantenimiento y los accidentes de carretera. Este proyecto parte de la base de investigación que se lleva a cabo en la LUT, tratando de mejorar el análisis de las muestras de asfalto, por lo que se realizarán las pruebas de estrés y encontrar soluciones para mejorar el asfalto en las carreteras polacas. Esto disminuiría notablemente el costo de mantenimiento. A pesar de no entrar en aspectos muy técnicos sobre el asfalto y su composición, se ha necesitado realizar un estudio profundo sobre todas sus características, para crear un código capaz de obtener los mejores resultados. Por estas razones, se ha desarrollado en Matlab, los algoritmos que permiten el estudio de los especímenes 3D de asfalto. Se ha utilizado este software, ya que Matlab es una poderosa herramienta matemática que permite operar con matrices para realización de operaciones rápidamente, permitiendo desarrollar un código específico para el tratamiento y procesamiento de imágenes en 3D. Gracias a esta herramienta, estos algoritmos realizan procesos tales como, la segmentación de la imagen 3D, pre y post procesamiento de la imagen, filtrado o todo tipo de análisis microestructural de las muestras de asfalto que se están estudiando. El código presentado para la segmentación de las muestras de asfalto 3D es menos complejo en su diseño y desarrollo, debido a las herramientas de procesamiento de imágenes que incluye Matlab, que facilitan significativamente la tarea de programación, así como el método de segmentación utilizado. Respecto al código, este ha sido diseñado teniendo en cuenta el objetivo de facilitar el trabajo de análisis y estudio de las imágenes en 3D de las muestras de asfalto. Por lo tanto, el principal objetivo es el de crear una herramienta para el estudio de este código, por ello fue desarrollado para que pueda ser integrado en un entorno visual, de manera que sea más fácil y simple su utilización. Ese es el motivo por el cual todos estos algoritmos y funciones, que ha sido desarrolladas, se integrarán en una herramienta visual que se ha desarrollado con el GUIDE de Matlab. Esta herramienta ha sido creada en colaboración con Jorge Vega, y fue desarrollada en su proyecto final de carrera, cuyo título es: Segmentación microestructural de Imágenes en 3D de la muestra de asfalto utilizando Matlab. En esta herramienta se ha utilizado todo las funciones programadas en este proyecto, y tiene el objetivo de desarrollar una herramienta que permita crear un entorno gráfico intuitivo y de fácil uso para el estudio de las muestras de 3D de asfalto. Este proyecto se ha dividido en 4 capítulos, en un primer lugar estará la introducción, donde se presentarán los aspectos más importante que se va a componer el proyecto. En el segundo capítulo se presentarán todos los datos técnicos que se han tenido que estudiar para desarrollar la herramienta, entre los que cabe los tres temas más importantes que se han estudiado en este proyecto: materiales asfálticos, los principios de la tomografías 3D y el procesamiento de imágenes. Esta será la base para el tercer capítulo, que expondrá la metodología utilizada en la elaboración del código, con la explicación del entorno de trabajo utilizado en Matlab y todas las funciones de procesamiento de imágenes utilizadas. Además, se muestra todo el código desarrollado, así como una descripción teórica de los métodos utilizados para el pre-procesamiento y segmentación de las imagenes en 3D. En el capítulo 4, se mostrarán los resultados obtenidos en el estudio de una de las muestras de asfalto, y, finalmente, el último capítulo se basa en las conclusiones sobre el desarrollo de este proyecto. En este proyecto se ha llevado han realizado todos los puntos que se establecieron como punto de partida en el anteproyecto para crear la herramienta, a pesar de que se ha dejado para futuros proyectos nuevas posibilidades de este codigo, como por ejemplo, la detección automática de las diferentes regiones de una muestra de asfalto debido a su composición. Como se muestra en este proyecto, las técnicas de procesamiento de imágenes se utilizan cada vez más en multitud áreas, como pueden ser industriales o médicas. En consecuencia, este tipo de proyecto tiene multitud de posibilidades, y pudiendo ser la base para muchas nuevas aplicaciones que se puedan desarrollar en un futuro. Por último, se concluye que este proyecto ha contribuido a fortalecer las habilidades de programación, ampliando el conocimiento de Matlab y de la teoría de procesamiento de imágenes. Del mismo modo, este trabajo proporciona una base para el desarrollo de un proyecto más amplio cuyo alcance será una herramienta que puedas ser utilizada por el equipo de investigación de la Universidad Tecnológica de Lodz y en futuros proyectos. ABSTRACT In this project has been developed one code in MATLAB to process X-ray tomographic 3D images of asphalt specimens. These images 3D has been taken by a research team of the Lodz University of Technology (LUT). The aim of this project is to create a tool that can be used to study differents asphalt specimen and can be used to study them after stress tests undergoing the samples. With the final goal to find solutions to the degradation suffered roads in Poland due to differents causes, like weather conditions. The degradation of the roads is an issue that has been investigated many years ago, due to strong degradation suffered caused by various factors such as climate, poor maintenance or excessive traffic in some cases. It is in Poland where these three factors make the composition of many roads degrade rapidly, especially due to the weather conditions suffered along the year, with temperatures ranging from 30 o C in summer to -20 ° C in winter. This causes the roads suffers a lot and asphalt rises shortly after putting, increasing maintenance costs and road accident. This project part of the base that research is taking place at the LUT, in order to better analyze the asphalt specimens, they are tested for stress and find solutions to improve the asphalt on Polish roads. This would decrease remarkable maintenance cost. Although this project will not go into the technical aspect as asphalt and composition, but it has been required a deep study about all of its features, to create a code able to obtain the best results. For these reasons, there have been developed in Matlab, algorithms that allow the study of 3D specimens of asphalt. Matlab is a powerful mathematical tool, which allows arrays operate fastly, allowing to develop specific code for the treatment and processing of 3D images. Thus, these algorithms perform processes such as the multidimensional matrix sgementation, pre and post processing with the same filtering algorithms or microstructural analysis of asphalt specimen which being studied. All these algorithms and function that has been developed to be integrated into a visual tool which it be developed with the GUIDE of Matlab. This tool has been created in the project of Jorge Vega which name is: Microstructural segmentation of 3D images of asphalt specimen using Matlab engine. In this tool it has been used all the functions programmed in this project, and it has the aim to develop an easy and intuitive graphical environment for the study of 3D samples of asphalt. This project has been divided into 4 chapters plus the introduction, the second chapter introduces the state-of-the-art of the three of the most important topics that have been studied in this project: asphalt materials, principle of X-ray tomography and image processing. This will be the base for the third chapter, which will outline the methodology used in developing the code, explaining the working environment of Matlab and all the functions of processing images used. In addition, it will be shown all the developed code created, as well as a theoretical description of the methods used for preprocessing and 3D image segmentation. In Chapter 4 is shown the results obtained from the study of one of the specimens of asphalt, and finally the last chapter draws the conclusions regarding the development of this project.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management.

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

A new similarity function for generalized trapezoidal fuzzy numbers

Numerous authors have proposed functions to quantify the degree of similarity between two fuzzy numbers using various descriptive parameters, such as the geometric distance, the distance between the centers of gravity or the perimeter. However, these similarity functions have drawback for specific situations. We propose a new similarity measure for generalized trapezoidal fuzzy numbers aimed at overcoming such drawbacks. This new measure accounts for the distance between the centers of gravity and the geometric distance but also incorporates a new term based on the shared area between the fuzzy numbers. The proposed measure is compared against other measures in the literature.

Nitrous oxide emissions from European agriculture - an analysis of variability and drivers of emissions from field experiments

Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logarden in Sweden, Maulde in Belgium CE1, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Godollo in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha−1yr−1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important deter- minant of emissions, accounting for 15 % of the variance (using linear regression) in the data from the arable sites (p<0.0001), and 77 % in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission fac- tors. Variability of N2O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation

Multidimensional, multislaces, and multiscale MRI for quality evaluation in food.

InsideFood explicitly aims at measuring food microstructure, the spatial distribution of food components within foods, with state of the art tomographic, spectroscopic and texture measurement techniques including X-ray micro-and nano CT, MRI,OCT, NMR, TRS and SRS, and acoustic emission. Nutritional quality (sugar and gluten free cereal products), sensory quality (texture of all foods) and safety (foreign material detection in cereal products) are considered. Online and inline techniques including NMR, MRI, TRS, SRS and X-ray imaging to visualise and monitor structure will be developed.

AVR adjustment of Synchronous Generators in Weak Grids under Faulty Conditions.

In weak grids, an important problem with voltage stability and protections coordination of power plants exists. This problem appears because all the generation groups are connected to the same bus bar. As a result, if a fault occurs in any of the generation groups, or in the bus bar that connect them, the system voltage will have large oscillations. Hence, in weak grids the correct adjustment of AVR (Automatic Voltage Regulator) is critical. In this work an experimental study of differents AVR adjustments against fault in weak grids is described.

Evaluation of the Grounding Circuit Measurements for Stator Ground-Fault Location of Synchronous Generators

Locating stator-winding ground faults accurately is a very difficult task. In this paper the grounding circuit measurements are evaluated in order to obtain information about the stator ground-fault location in synchronous generators. In power generators grounded through a high impedance, the relation between the neutral voltage and the phase voltage provide a first estimation of the fault location. The location error by using this ratio depends on the fault resistance and the value of the capacitance to ground of the stator winding. However, the error added by ignoring the value of the fault resistance is the most relevant term. This location estimation and the location error have been evaluated through the data of a real synchronous machine.

Consideration of Multi-Phase Criterion in the Differential Protection Algorithm for High-Impedance Grounded Synchronous Generators

The generator differential protection is one of the most important electrical protections of synchronous generator stator windings. Its operation principle is based on the comparison of the input current and output current at each phase winding. Unwanted trip commands are usually caused by CT saturation, wrong CT selection, or the fact that they may come from different manufacturers. In generators grounded through high impedance, only phase-to-phase or three-phase faults can be detected by the differential protection. This kind of fault causes differential current to flow in, at least, two phases of the winding. Several cases of unwanted trip commands caused by the appearance of differential current in only one phase of the generator have been reported. In this paper multi-phase criterion is proposed for generator differential protection algorithm when applied to high impedance grounded generators.

Depth perceptual video coding for free viewpoint video based on H.264/AVC

A novel scheme for depth sequences compression, based on a perceptual coding algorithm, is proposed. A depth sequence describes the object position in the 3D scene, and is used, in Free Viewpoint Video, for the generation of synthetic video sequences. In perceptual video coding the human visual system characteristics are exploited to improve the compression efficiency. As depth sequences are never shown, the perceptual video coding, assessed over them, is not effective. The proposed algorithm is based on a novel perceptual rate distortion optimization process, assessed over the perceptual distortion of the rendered views generated through the encoded depth sequences. The experimental results show the effectiveness of the proposed method, able to obtain a very considerable improvement of the rendered view perceptual quality.

MAIA: an event-based modular architecture for intelligent agents

Online services are no longer isolated. The release of public APIs and technologies such as web hooks are allowing users and developers to access their information easily. Intelligent agents could use this information to provide a better user experience across services, connecting services with smart automatic. behaviours or actions. However, agent platforms are not prepared to easily add external sources such as web services, which hinders the usage of agents in the so-called Evented or Live Web. As a solution, this paper introduces an event-based architecture for agent systems, in accordance with the new tendencies in web programming. In particular, it is focused on personal agents that interact with several web services. With this architecture, called MAIA, connecting to new web services does not involve any modification in the platform.