Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin.

Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.

Application of the agency theory for the analysis of performance-based mechanisms in road management

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte, y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper develops a model based on agency theory to analyze road management systems (under the different contract forms available today) that employ a mechanism of performance indicators to establish the payment of the agent. The base assumption is that of asymmetric information between the principal (Public Authorities) and the agent (contractor) and the risk aversion of this latter. It is assumed that the principal may only measure the agent?s performance indirectly and by means of certain performance indicators that may be verified by the authorities. In this model there is presumed to be a relation between the efforts made by the agent and the performance level measured by the corresponding indicators, though it is also considered that there may be dispersion between both variables that gives rise to a certain degree of randomness in the contract. An analysis of the optimal contract has been made on the basis of this model and in accordance with a series of parameters that characterize the economic environment and the particular conditions of road infrastructure. As a result of the analysis made, it is considered that an optimal contract should generally combine a fixed component and a payment in accordance with the performance level obtained. The higher the risk aversion of the agent and the greater the marginal cost of public funds, the lower the impact of this performance-based payment. By way of conclusion, the system of performance indicators should be as broad as possible but should not overweight those indicators that encompass greater randomness in their results.

Multi-objective Aerodynamic Optimization of High-speed Trains in Tunnels

A genetic algorithm (GA) is employed for the multi-objective shape optimization of the nose of a high-speed train. Aerodynamic problems observed at high speeds become still more relevant when traveling along a tunnel. The objective is to minimize both the aerodynamic drag and the amplitude of the pressure gradient of the compression wave when a train enters a tunnel. The main drawback of GA is the large number of evaluations need in the optimization process. Metamodels-based optimization is considered to overcome such problem. As a result, an explicit relationship between pressure gradient and geometrical parameters is obtained.

A Knowledge Model for Automatic Configuration of Traffic Messages

This paper describes a knowledge model for a configuration problem in the do-main of traffic control. The goal of this model is to help traffic engineers in the dynamic selection of a set of messages to be presented to drivers on variable message signals. This selection is done in a real-time context using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based solution that implements two abstract problem solving methods according to a model-based approach recently proposed in the knowledge engineering field. Finally, the paper presents a discussion about the advantages and drawbacks found for this problem as a consequence of the applied knowledge modeling ap-proach.

Modeling Commercial Knowledge to Develop Advanced Agent-based Marketplaces for E-commerce

This paper argues about the utility of advanced knowledge-based techniques to develop web-based applications that help consumers in finding products within marketplaces in e-commerce. In particular, we describe the idea of model-based approach to develop a shopping agent that dynamically configures a product according to the needs and preferences of customers. Finally, the paper summarizes the advantages provided by this approach.

Real-time determination of airspace wind speed field based on FDR = Determinación en tiempo real del campo de velocidad del viento basado en registradores de datos de vuelo

El estudio del comportamiento de la atmósfera ha resultado de especial importancia tanto en el programa SESAR como en NextGen, en los que la gestión actual del tránsito aéreo (ATM) está experimentando una profunda transformación hacia nuevos paradigmas tanto en Europa como en los EE.UU., respectivamente, para el guiado y seguimiento de las aeronaves en la realización de rutas más eficientes y con mayor precisión. La incertidumbre es una característica fundamental de los fenómenos meteorológicos que se transfiere a la separación de las aeronaves, las trayectorias de vuelo libres de conflictos y a la planificación de vuelos. En este sentido, el viento es un factor clave en cuanto a la predicción de la futura posición de la aeronave, por lo que tener un conocimiento más profundo y preciso de campo de viento reducirá las incertidumbres del ATC. El objetivo de esta tesis es el desarrollo de una nueva técnica operativa y útil destinada a proporcionar de forma adecuada y directa el campo de viento atmosférico en tiempo real, basada en datos de a bordo de la aeronave, con el fin de mejorar la predicción de las trayectorias de las aeronaves. Para lograr este objetivo se ha realizado el siguiente trabajo. Se han descrito y analizado los diferentes sistemas de la aeronave que proporcionan las variables necesarias para obtener la velocidad del viento, así como de las capacidades que permiten la presentación de esta información para sus aplicaciones en la gestión del tráfico aéreo. Se ha explorado el uso de aeronaves como los sensores de viento en un área terminal para la estimación del viento en tiempo real con el fin de mejorar la predicción de las trayectorias de aeronaves. Se han desarrollado métodos computacionalmente eficientes para estimar las componentes horizontales de la velocidad del viento a partir de las velocidades de las aeronaves (VGS, VCAS/VTAS), la presión y datos de temperatura. Estos datos de viento se han utilizado para estimar el campo de viento en tiempo real utilizando un sistema de procesamiento de datos a través de un método de mínima varianza. Por último, se ha evaluado la exactitud de este procedimiento para que esta información sea útil para el control del tráfico aéreo. La información inicial proviene de una muestra de datos de Registradores de Datos de Vuelo (FDR) de aviones que aterrizaron en el aeropuerto Madrid-Barajas. Se dispuso de datos de ciertas aeronaves durante un periodo de más de tres meses que se emplearon para calcular el vector viento en cada punto del espacio aéreo. Se utilizó un modelo matemático basado en diferentes métodos de interpolación para obtener los vectores de viento en áreas sin datos disponibles. Se han utilizado tres escenarios concretos para validar dos métodos de interpolación: uno de dos dimensiones que trabaja con ambas componentes horizontales de forma independiente, y otro basado en el uso de una variable compleja que relaciona ambas componentes. Esos métodos se han probado en diferentes escenarios con resultados dispares. Esta metodología se ha aplicado en un prototipo de herramienta en MATLAB © para analizar automáticamente los datos de FDR y determinar el campo vectorial del viento que encuentra la aeronave al volar en el espacio aéreo en estudio. Finalmente se han obtenido las condiciones requeridas y la precisión de los resultados para este modelo. El método desarrollado podría utilizar los datos de los aviones comerciales como inputs utilizando los datos actualmente disponibles y la capacidad computacional, para proporcionárselos a los sistemas ATM donde se podría ejecutar el método propuesto. Estas velocidades del viento calculadas, o bien la velocidad respecto al suelo y la velocidad verdadera, se podrían difundir, por ejemplo, a través del sistema de direccionamiento e informe para comunicaciones de aeronaves (ACARS), mensajes de ADS-B o Modo S. Esta nueva fuente ayudaría a actualizar la información del viento suministrada en los productos aeronáuticos meteorológicos (PAM), informes meteorológicos de aeródromos (AIRMET), e información meteorológica significativa (SIGMET). ABSTRACT The study of the atmosphere behaviour is been of particular importance both in SESAR and NextGen programs, where the current air traffic management (ATM) system is undergoing a profound transformation to the new paradigms both in Europe and the USA, respectively, to guide and track aircraft more precisely on more efficient routes. Uncertainty is a fundamental characteristic of weather phenomena which is transferred to separation assurance, flight path de-confliction and flight planning applications. In this respect, the wind is a key factor regarding the prediction of the future position of the aircraft, so that having a deeper and accurate knowledge of wind field will reduce ATC uncertainties. The purpose of this thesis is to develop a new and operationally useful technique intended to provide adequate and direct real-time atmospheric winds fields based on on-board aircraft data, in order to improve aircraft trajectory prediction. In order to achieve this objective the following work has been accomplished. The different sources in the aircraft systems that provide the variables needed to derivate the wind velocity have been described and analysed, as well as the capabilities which allow presenting this information for air traffic management applications. The use of aircraft as wind sensors in a terminal area for real-time wind estimation in order to improve aircraft trajectory prediction has been explored. Computationally efficient methods have been developed to estimate horizontal wind components from aircraft velocities (VGS, VCAS/VTAS), pressure, and temperature data. These wind data were utilized to estimate a real-time wind field using a data processing approach through a minimum variance method. Finally, the accuracy of this procedure has been evaluated for this information to be useful to air traffic control. The initial information comes from a Flight Data Recorder (FDR) sample of aircraft landing in Madrid-Barajas Airport. Data available for more than three months were exploited in order to derive the wind vector field in each point of the airspace. Mathematical model based on different interpolation methods were used in order to obtain wind vectors in void areas. Three particular scenarios were employed to test two interpolation methods: a two-dimensional one that works with both horizontal components in an independent way, and also a complex variable formulation that links both components. Those methods were tested using various scenarios with dissimilar results. This methodology has been implemented in a prototype tool in MATLAB © in order to automatically analyse FDR and determine the wind vector field that aircraft encounter when flying in the studied airspace. Required conditions and accuracy of the results were derived for this model. The method developed could be fed by commercial aircraft utilizing their currently available data sources and computational capabilities, and providing them to ATM system where the proposed method could be run. Computed wind velocities, or ground and true airspeeds, would then be broadcasted, for example, via the Aircraft Communication Addressing and Reporting System (ACARS), ADS-B out messages, or Mode S. This new source would help updating the wind information furnished in meteorological aeronautical products (PAM), meteorological aerodrome reports (AIRMET), and significant meteorological information (SIGMET).

A discrete spectral model for intermediate crack debonding in FRP-strengthened RC beams

One of the common failure modes of reinforced concrete (RC) beams strengthened in flexure with a bonded fibre-reinforced polymer (FRP) is intermediate crack (IC) debonding, which is originated at a critical section in the vicinity of flexural cracks and propagates to a plate end. Despite considerable research over the last years, few reliable and simplified IC debonding strength models have been developed. This paper firstly presents a one-dimensional model based on the discrete crack approach for concrete and the spectral element method for the numerical simulation of the IC debonding process. The progressive formation of flexural cracks and subsequent concrete-FRP interfacial debonding is formulated by the introduction of a new element able to represent both phenomena simultaneously without perturbing the numerical procedure. Furthermore, with the proposed model, high frequency dynamic response for these kinds of structures can also be obtained in a very simple and non-expensive way, which makes this procedure very useful as a tool for diagnoses and detection of debonding in its initial stage by monitoring the change in local dynamic characteristics.

Initializing the DSSAT-Century model: inverse calibration of carbon pools from apparent soil N mineralization

The CENTURY soil organic matter model was adapted for the DSSAT (Decision Support System for Agrotechnology Transfer), modular format in order to better simulate the dynamics of soil organic nutrient processes (Gijsman et al., 2002). The CENTURY model divides the soil organic carbon (SOC) into three hypothetical pools: microbial or active material (SOC1), intermediate (SOC2) and the largely inert and stable material (SOC3) (Jones et al., 2003). At the beginning of the simulation, CENTURY model needs a value of SOC3 per soil layer which can be estimated by the model (based on soil texture and management history) or given as an input. Then, the model assigns about 5% and 95% of the remaining SOC to SOC1 and SOC2, respectively. The model performance when simulating SOC and nitrogen (N) dynamics strongly depends on the initialization process. The common methods (e.g. Basso et al., 2011) to initialize SOC pools deal mostly with carbon (C) mineralization processes and less with N. Dynamics of SOM, SOC, and soil organic N are linked in the CENTURY-DSSAT model through the C/N ratio of decomposing material that determines either mineralization or immobilization of N (Gijsman et al., 2002). The aim of this study was to evaluate an alternative method to initialize the SOC pools in the DSSAT-CENTURY model from apparent soil N mineralization (Napmin) field measurements by using automatic inverse calibration (simulated annealing). The results were compared with the ones obtained by the iterative initialization procedure developed by Basso et al., 2011.

RESSIST: a research object-based recommender system

The scientific method is a methodological approach to the process of inquiry { in which empirically grounded theory of nature is constructed and verified [14]. It is a hard, exhaustive and dedicated multi-stage procedure that a researcher must perform to achieve valuable knowledge. Trying to help researchers during this process, a recommender system, intended as a researcher assistant, is designed to provide them useful tools and information for each stage of the procedure. A new similarity measure between research objects and a representational model, based on domain spaces, to handle them in dif ferent levels are created as well as a system to build them from OAI-PMH (and RSS) resources. It tries to represents a sound balance between scientific insight into individual scientific creative processes and technical implementation using innovative technologies in information extraction, document summarization and semantic analysis at a large scale.

A simple mathematical model that describes the growth of the area and the number of total and viable cells in yeast colonies

We propose a model, based on the Gompertz equation, to describe the growth of yeasts colonies on agar medium. This model presents several advantages: (i) one equation describes the colony growth, which previously needed two separate ones (linear increase of radius and of the squared radius); (ii) a similar equation can be applied to total and viable cells, colony area or colony radius, because the number of total cells in mature colonies is proportional to their area; and (iii) its parameters estimate the cell yield, the cell concentration that triggers growth limitation and the effect of this limitation on the specific growth rate. To elaborate the model, area, total and viable cells of 600 colonies of Saccharomyces cerevisiae, Debaryomyces fabryi, Zygosaccharomyces rouxii and Rhodotorula glutinis have been measured. With low inocula, viable cells showed an initial short exponential phase when colonies were not visible. This phase was shortened with higher inocula. In visible or mature colonies, cell growth displayed Gompertz-type kinetics. It was concluded that the cells growth in colonies is similar to liquid cultures only during the first hours, the rest of the time they grow, with near-zero specific growth rates, at least for 3 weeks.

Linked-data based domain-specific sentiment lexicons

In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languages for two domains. We used existing collections of reviews from Trip Advisor, Amazon, the Stanford Network Analysis Project and the OpinRank Review Dataset. We use an RDF model based on the lemon and Marl formats to represent the lexicons. We describe the methodology that we applied to generate the domain-specific lexicons and we provide access information to our datasets.

Networks based on QKD and weakly trusted repeaters

We study how to use quantum key distribution (QKD) in common optical network infrastructures and propose a method to overcome its distance limitations. QKD is the first technology offering information theoretic secret-key distribution that relies only on the fundamental principles of quantum physics. Point-to-point QKD devices have reached a mature industrial state; however, these devices are severely limited in distance, since signals at the quantum level (e.g. single photons) are highly affected by the losses in the communication channel and intermediate devices. To overcome this limitation, intermediate nodes (i.e. repeaters) are used. Both, quantum-regime and trusted, classical, repeaters have been proposed in the QKD literature, but only the latter can be implemented in practice. As a novelty, we propose here a new QKD network model based on the use of not fully trusted intermediate nodes, referred as weakly trusted repeaters. This approach forces the attacker to simultaneously break several paths to get access to the exchanged key, thus improving significantly the security of the network. We formalize the model using network codes and provide real scenarios that allow users to exchange secure keys over metropolitan optical networks using only passive components.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Almacenamiento de energía térmica por calor latente en los edificios: bases para la optimización de aplicaciones pasivas, opacas y traslúcidas

La principal motivación para la elección del tema de la tesis es nuestra realidad energética y ambiental. Y más específicamente, la necesidad urgente de dar una respuesta a esta realidad desde el sector de la edificación. Por lo que, el trabajo parte de la búsqueda de soluciones pasivas que ayuden a la reducción del consumo energético y de las emisiones de C02 de los edificios, tanto nuevos como existentes. El objeto de estudio son aplicaciones innovadoras, basadas en el uso de materiales reactivos, con un efecto térmico de memoria bidireccional. La energía es un elemento imprescindible para el desarrollo. Sin embargo, el modelo energético predominante, basado principalmente en la utilización de combustibles de origen fósil, es uno de los importantes responsables del deterioro ambiental que sufre el planeta. Además, sus reservas son limitadas y están concentradas en unas pocas regiones del mundo, lo que genera problemas de dependencia, competitividad y de seguridad de suministro. Dado el gran potencial de ahorro energético del sector de la edificación, la Unión Europea en sus directivas enfatiza la necesidad de mejorar la eficiencia energética de los edificios. Añadiendo, además, la obligatoriedad de desarrollar edificios “energía casi nula”, cuyo prerrequisito es tener un muy alto rendimiento energético. En España, los edificios son responsables del 31% del consumo de energía primaria. La mayor parte de este consumo se relaciona a la utilización de sistemas activos de acondicionamiento. Una medida efectiva para reducir la demanda es mejorar la envolvente. Sin embargo, hay que buscar estrategias adicionales para aumentar aún más la eficiencia de los edificios nuevos y existentes. Para los climas de España, el uso de la inercia térmica ha probado ser una estrategia válida. Sin embargo, su funcionamiento está vinculado al peso y al volumen de los materiales utilizados. Esto limita sus posibilidades en la rehabilitación energética y en los nuevos edificios basados en la construcción ligera. Una alternativa es el uso de aplicaciones de almacenamiento térmico por calor latente, utilizando materiales de cambio de fase (PCM). Los PCM son sustancias con un muy alto calor de fusión, capaces de almacenar una gran cantidad de energía térmica sin requerir aumentos significativos de peso o volumen. Estas características los hacen idóneos para reducir el consumo relacionado con el acondicionamiento térmico, en edificios nuevos y existentes. En la parte preliminar de la investigación, se encontró que para lograr un aprovechamiento óptimo de las aplicaciones con PCM es necesario tener un conocimiento profundo de su funcionamiento y de las variables del sistema. De ahí que el objetivo principal de la presente tesis sea: establecer las bases para la optimizatión integral de las aplicaciones con almacenamiento de energía térmica por calor latente, identificando y validando sus variables más relevantes. La investigación consta de tres partes. La primera, documental, sistematizando y jerarquizando la información científica publicada; la segunda, numérica, basada en un análisis paramétrico de una aplicación con PCM, utilizando simulaciones térmicas; y la tercera, experimental, monitorizando el funcionamiento térmico y energético de diferentes aplicaciones con PCM en módulos a escala real. Los resultados brindan un más profundo entendimiento del funcionamiento de las aplicaciones evaluadas. Han permitido identificar sus variables relevantes, cuantificar su influencia, y determinar condiciones óptimas para su utilización así como situaciones en las que sería muy difícil justificar su uso. En el proceso, se realizó la caracterización térmica y energética de aplicaciones con PCM, tanto opacas como traslúcidas. Además, se ha encontrado que las aplicaciones con PCM son capaces de aumentar la eficiencia energética inclusive en recintos con diseños optimizados, demostrando ser una de las estrategias adecuadas para lograr el muy alto desempeño energético requerido en los edificios energía nula. ABSTRACT The main motivation for choosing the theme of the thesis is our energy and environmental reality. And more specifically, the urgent need to respond to this reality from the building sector. This is why, the work start with the search of passive solutions that help reduce energy consumption and C02 emissions of buildings, in both new and existing ones. The object of study is innovative applications based on the use of responsive materials, with bidirectional thermal memory. Energy is an essential element for development. However, the predominant energy model, based primarily on the use of fossil fuels, is one of the major responsible for the environmental deterioration of the planet, the cause of most of the CO2 emissions. Furthermore, reserves of fossil fuels are limited and are concentrated in a few regions of the world, which creates issues related to dependency, competitiveness, and security of supply. Given the large potential for energy savings in the building sector, the European Union in its directives emphasizes the need to improve energy efficiency in buildings. Also, adding the obligation to develop "nearly zero energy" buildings, whose first prerequisite is to achieve a very high energy efficiency. In Spain, buildings are responsible for 31% of primary energy consumption and most of this consumption is related to the used of HVAC systems. One of the most effective measures to reduce demand is to improve the envelope. However, it is necessary to look for additional strategies to further increase the efficiency of new and existing buildings. For the predominant climates in Spain, use of the thermal inertia may be a valid strategy. Nevertheless, its operation is linked to weight and volume of the materials used. This limits their possibilities in the existing buildings energy retrofitting and in the new buildings based on lightweight construction. An alternative is the use of latent heat thermal energy storage applications (LHTES), using phase change materials (PCM). PCM are substances with a high heat of fusion, capable of storing a large amount of thermal energy without requiring significant increases in weight or volume. These features make them ideal for reducing energy consumption associated with thermal conditioning in both new and existing buildings. In the preliminary part of the investigation, it was found that to get optimum utilization of the PCM applications is needed to have a deep understanding of its operation and, in particular, how the system variables affect its performance. Hence, the main objective of this thesis is: to establish the basis for the integral optimization of applications with latent heat thermal energy storage, identifying and validating the most relevant variables. The research comprises of three parts. The first, documentary, systematizing and prioritizing published scientific information. The second, numeric, based on a parametric analysis of an application PCM using thermal simulations. The third, experimental, monitoring the thermal and energy performance of different applications with PCM on real scale test cells. The results provide a complete understanding of the functioning of the evaluated LHTES application. They have allowed to identify their relevant variables, quantify their influence and determine optimum conditions for use as well as situations where it would be very difficult to justify its use. In the process, it was carried out the power and thermal characterization of various opaque and translucent PCM applications. Furthermore, it has been found that applications with PCM can increase the energy efficiency, even in buildings with optimized designs; proving to be one of the appropriate measures to achieve the high energy performance required in zero energy buildings.

Location of bioelectricity plants in the Madrid Community based on triticale crop: a multicriteria methodology

This paper presents a work whose objective is, first, to quantify the potential of the triticale biomass existing in each of the agricultural regions in the Madrid Community through a crop simulation model based on regression techniques and multiple correlation. Second, a methodology for defining which area has the best conditions for the installation of electricity plants from biomass has been described and applied. The study used a methodology based on compromise programming in a discrete multicriteria decision method (MDM) context. To make a ranking, the following criteria were taken into account: biomass potential, electric power infrastructure, road networks, protected spaces, and urban nuclei surfaces. The results indicate that, in the case of the Madrid Community, the Campiña region is the most suitable for setting up plants powered by biomass. A minimum of 17,339.9 tons of triticale will be needed to satisfy the requirements of a 2.2 MW power plant. The minimum range of action for obtaining the biomass necessary in Campiña region would be 6.6 km around the municipality of Algete, based on Geographic Information Systems. The total biomass which could be made available in considering this range in this region would be 18,430.68 t.