The power usage of the communication technology industry and the consistent energy-related pollution are becoming major societal and economic concerns. These concern stimulated academia and industry to an intense activity in the new research area of green cellular networks. Bandwidth Efficiency (BE) is one of the most important metrics to select candidate technologies for next-generation wireless communications systems. Nevertheless, the important goal is to design new innovative network architecture and technologies needed to encounter the explosive development in cellular data demand without increasing the power consumption. As a result, Energy Efficiently (EE) has become another significant metric for evaluating the performance of wireless communications systems. MIMO technology has drawn lots of attention in wireless communication, as it gives substantial increases in link range and throughput without an additional increase in bandwidth or transmits power. Multi-user MIMO (MU-MIMO) regarded when evolved Base Station equipped with multiple antennas communicates with several User Terminal (UEs) at the same time. MU-MIMO is capable of improving either the reliability or the BE by improving either the multiplexing gains or diversity gains. A proposed new idea in MU-MIMO refers to the system that uses hundreds of antennas to serve dozens of UEs simultaneously. This so-called, Large Scale-MIMO (LS MIMO) regarded as a candidate technique for future wireless communication systems. An analysis is conducted to investigate the performance of the proposed uplink and downlink of LS MIMO systems with different linear processing techniques at the base station. The most common precoding and receive combining are considered: minimum mean squared error (MMSE), maximum ratio transmission/combining (MRT/MRC), and zero-forcing (ZF)processing. The fundamental problems answered on how to select the number of (BS) antennas M, number of active (UEs) K, and the transmit power to cover a given area with maximal EE. The EE is defined as the number of bits transferred per Joule of energy. A new power consumption model is proposed to emphasise that the real power scales faster with M and K than scaling linearly. The new power consumption model is utilised for deriving closed-form EE maximising values of the number of BS antennas, number of active UEs and transmit power under the assumption that ZF processing is deployed in the uplink and downlink transmissions for analytic convenience. This analysis is then extended to the imperfect CSI case and to symmetric multi-cell scenarios. These expressions provide valuable design understandings on the interaction between systems parameters, propagation environment, and different components of the power consumption model. Analytical results are assumed only for ZF with perfect channel state information (CSI) to compute closed-form expression for the optimal number of UEs, number of BS antennas, and transmit power. Numerical results are provided (a) for all the investigated schemes with perfect CSI and in a single-cell scenario; (b) for ZF with imperfect CSI, and in a multi-cell scenario. The simulation results show that (a) an LS MIMO with 100 - 200 BS antennas are the correct number of antennas for energy efficiency maximisation; (b) these number of BS antennas should serve number of active UEs of the same size; (c) since the circuit power increases the transmit power should increase with number of BS antennas; (d) the radiated power antenna is in the range of 10-100 mW and decreases with number of BS antennas; (e) ZF processing provides the highest EE in all the scenarios due to active interference-suppression at affordable complexity. Therefore, these are highly relevant results that prove LS MIMO is the technique to achieve high EE in future cellular networks.

Orientador: Angelo Cataneo / Banca: Zacarias Xavier de Barros / Banca: Sergio A.Lunardelli Furchi / Banca: Wagner José Dizeró / Banca: Manoel Henrique Salgado / Resumo: Com o fenômeno da globalização e da unificação dos mercados, novas oportunidades de negócio surgiram, exigindo dos produtores o incremento da qualidade dos serviços e o controle preciso das operações, reduzindo o custo operacional. Neste novo cenário, as propriedades rurais estão passando por grandes mudanças, transformando-se em verdadeiras empresas rurais. Cada vez mais este novo modelo econômico prima pela qualidade e pela sustentabilidade do agronegócio. Para tal, é necessário um sistema que auxilie o produtor rural a administrar o seu negócio. A maioria dos estudos estão focados em levantamento financeiro e esquecem que é essencial para a agricultura definir o Balanço Energético e determinar a sua eficiência. Vários trabalhos propostos comparam duas formas produtivas em uma determinada região, mas não existe um estudo em nível nacional. O presente trabalho propõe um modelo de sistema de informação que abrange a parte energética do agronegócio, bem como o envio destas informações para uma base centralizada, a fim de obter o modelo energético rural brasileiro. Com isto, será possível determinar o Balanço Energético e as formas mais eficientes de plantio no agronegócio. O sistema proposto é dividido em dois módulos. O primeiro é voltado aos pequenos produtores rurais, no intuito de ajuda-los na administração rural, disponibilizando relatórios gerencias para que o produtor conheça o desempenho energético do sistema agrícola implantado, podendo maximizar os resultados energéticos e melhorar a eficiência da produção. O segundo módulo é composto de um software de analise de dados, recebendo os dados enviados pelos produtores e construindo uma base nacional de informação a respeito dos resultados energéticos, podendo comparar a eficiência dos sistemas de plantio... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: With the phenomenon of globalization and the unification of markets, new business opportunities have emerged, requiring producers to increase service quality and precise control of operations, reducing operating cost. In this new senary, farms are undergoing major changes, transforming themselves into true rural businesses. Increasingly, this new economic model strives for quality and sustainability of agribusiness. For such a system is needed to assist the farmer to manage your business. Most studies are focused on raising financial and forget that agriculture is essential to define the energy balance and determine its efficiency. Several studies comparing two proposed forms of production in a given region, but there is a nationwide study. This paper proposes a model of information system that covers the energy part of agribusiness, as well as sending this information to a centralized database in order to get the Brazilian rural energy model. With this, you can determine the energy balance and more efficient ways of planting in agribusiness. The proposed system is divided into two modules. The first is geared to small farmers in order to aid them in farm management, providing management reports for the producer to meet the energy performance of the agricultural system in place, the results can maximize energy and improve production efficiency. The second module consists of a software data analysis, receiving the data sent by the producers and building a national information regarding the results of energy and can compare the efficiency of cropping systems in certain regions or making a historical analysis, comparing performance over the years / Doutor

With an ever-increasing need to find alternative fuels to curb the use of oil in the world, many sources have been identified as alternative fuels. One of these sources is hydrogen. Hydrogen can be produced through an electro-chemical process. The objective of this report is to model an electrochemical process and determine gains and or losses in efficiency of the process by increasing or decreasing the temperature of the feed water. In order to make the process environmentally conscience, electricity from a geothermal plant will be used to power the electrolyzer. Using the renewable energy makes the process of producing hydrogen carbon free. Water considerations and a model of a geothermal plant were incorporated to achieve the objectives. The data show that there are optimal operating characteristics for electrolyzers. There is a 17% increase in efficiency by increasing the temperature from 20ºC to 80ºC. The greater the temperature the higher the efficiencies, but there are trade-offs with the required currents.

<p>In this work, an existing RAM generator is analysed and evaluated. Some of the aspects that were considered in the evaluation are the optimization of the basic SRAM cell, how the RAM generator can be ported to newer technologys, automating the simulation process and the creation of the workflow for the energy model.</p><p>One of the main focus of this thesis work is to optimize the basic SRAM cell. The SRAM cell which is used in the RAM generator is not optimized for area nor power. A compact layout is suggested which saves a lot of area and power. The technology that is used to create the RAM generator is old and a suitable way to port it to newer technology has also been found.</p><p>To create an energy model one has to simulate a lot of memories with a lot of data. This cannot be done in the traditional way of simulating circuits using the GUI. Hence an automation procedure has been suggested which can be made to work to create energy models by simulating the memories comprehensively.</p><p>Finally, basic ground work has been initiated by creating a workflow for the creation of the energy model.</p>

In this work, an existing RAM generator is analysed and evaluated. Some of the aspects that were considered in the evaluation are the optimization of the basic SRAM cell, how the RAM generator can be ported to newer technologys, automating the simulation process and the creation of the workflow for the energy model. One of the main focus of this thesis work is to optimize the basic SRAM cell. The SRAM cell which is used in the RAM generator is not optimized for area nor power. A compact layout is suggested which saves a lot of area and power. The technology that is used to create the RAM generator is old and a suitable way to port it to newer technology has also been found. To create an energy model one has to simulate a lot of memories with a lot of data. This cannot be done in the traditional way of simulating circuits using the GUI. Hence an automation procedure has been suggested which can be made to work to create energy models by simulating the memories comprehensively. Finally, basic ground work has been initiated by creating a workflow for the creation of the energy model.

Worldwide, the residential sector is a major consumer of energy. Both the rate at which we consume energy and our use of non-renewable energy resources have come under pressure to change. These changes may occur to some extent by conservation techniques. However, due to living standard expectations, these changes will primarily rely on technology. Many technological opportunities exist to reduce the conventional energy consumption and greenhouse gas (GHG) emissions of the residential sector, such as: improving energy efficiency, introducing alternative energy conversion technologies, and increasing the use of renewable energy resources. The accurate estimate of the impact that a new technology has on residential sector energy consumption and GHG emissions requires a versatile, reliable, detailed, and high-resolution analytical model. Such models account for the wide range of climate, energy supply, and housing stock characteristics, and are useful for decision makers to evaluate and parametrically compare a wide range of energy efficiency measures and technology strategies when applied to the residential sector. This dissertation presents the development of a new energy consumption and GHG emissions model of the Canadian residential sector. This new model is detailed with regard to the housing stock, comprehensive with regard to the treatment of end-uses (including thermodynamic behaviour and occupant behaviour), and possesses the capability, resolution, and accuracy to assess the impact upon energy consumption and GHG emissions due to the application of alternative and renewable energy technologies to the residential sector. The new model is titled the Canadian Hybrid Residential End-Use Energy and GHG Emissions Model (CHREM). The CHREM advances the state-of-the-art of residential sector energy consumption and GHG emissions modeling by three principal contributions: i) a database of 16,952 unique house descriptions of thermal envelope and energy conversion system information that statistically represent the Canadian housing stock; ii) a “hybrid” modeling approach that integrates the bottom-up statistical and engineering modeling methods to account for occupant behaviour, and provide the capacity to model alternative and renewable energy technologies, such as solar energy and energy storage systems; and iii) a method for the accumulation and treatment of energy and GHG emissions results.

Cement production is an energy intensive process. In South Africa the cost of energy increased since 2006, while cement sales have dropped dramatically. It has become important to focus on methods to optimise energy consumption to achieve cost savings in the cement industry. Various methods of reducing production cost by improving energy efficiency are available, but require extended installation periods and high initial capital expenditure. Other methods such as operational optimisation can reduce production cost, but offer limited savings. The aim of this study is to integrate the optimisation of multiple component operations to improve savings and reduce interruption during implementation. Although integrated optimisation models have been developed, no literature could be found on the application of these models in the cement industry. This thesis reports on the development and implementation of an energy management system at four South African cement plants. The total electricity costs were reduced without installing costly infrastructure upgrades. The results summarise the success of the improved production planning. A conclusion regarding the feasibility of this implementation is compiled by comparing the savings achieved by the implementation of the energy management system to other energy saving methods. Recommendations are also made for further study and the implementation of the energy management system in similar industries. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013.

Cement production is an energy intensive process. In South Africa the cost of energy increased since 2006, while cement sales have dropped dramatically. It has become important to focus on methods to optimise energy consumption to achieve cost savings in the cement industry. Various methods of reducing production cost by improving energy efficiency are available, but require extended installation periods and high initial capital expenditure. Other methods such as operational optimisation can reduce production cost, but offer limited savings. The aim of this study is to integrate the optimisation of multiple component operations to improve savings and reduce interruption during implementation. Although integrated optimisation models have been developed, no literature could be found on the application of these models in the cement industry. This thesis reports on the development and implementation of an energy management system at four South African cement plants. The total electricity costs were reduced without installing costly infrastructure upgrades. The results summarise the success of the improved production planning. A conclusion regarding the feasibility of this implementation is compiled by comparing the savings achieved by the implementation of the energy management system to other energy saving methods. Recommendations are also made for further study and the implementation of the energy management system in similar industries. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013.

The astrophysical data of the last two decades have allowed cosmologists to conclude that the present Universe is accelerating. The research carried out to find the origin of this phenomenon has led to the creation of a vast number of dark energy and modified gravity theories, of which the simplest is the ˄CDM model. The latter is, however, plagued with very difficult problems awaiting a solution. The work here presented seeks to contribute to the discussion of the possible explanation for the Cosmos' acceleration and other important questions in modern cosmology using the newest astrophysical observations available. This thesis starts by exploring a dark energy model dubbed thawing quintessence which is characterised by allowing a non constant ratio of pressure to density for dark energy that is however still close to -1 for most of the cosmological evolution, shifting away from this value when the domination of the radiation and matter components fades away. The findings are the most up-to-date constraints for which this model gives a viable theory for dark energy, including a bound on the equation of state at present of w < -0:88. This exact approach was contrasted with the use of an approximate equation-of-state parametrisation for thawing theories. The analysis also includes different parametrisation choices, and comments on the accuracy of the constraints imposed by CMB anisotropies alone. Next, the cosmology of hybrid metric-Palatini gravity is presented. This is a type of Modified Gravity theory in which the Lagrangian density for the gravitational action is a function of the Ricci scalars of both the connection and the metric. The background evolution of two models of this kind is examined explicitly showing the recovery of standard General Relativity at late times. The maximum deviation from the gravitational constant G at early times is constrained using a combination of geometrical data, finding it to be around 1%. A designer scenario, also introduced under the hybrid metric-Palatini formulation, is then used to explore to what extent early modifications of gravity, which become significant after recombination but then decay towards the present, can be constrained by current and future cosmological observations. This model is embedded in the effective field theory description of Horndeski scalar-tensor gravity with an early-time decoupling of the gravitational modification. Applying cosmological data, the constraints on the early-time deviations from General Relativity are obtained. These are dependent on the redshift at which the oscillations in the slip between the gravitational potentials are turned on. For zon = 1000, the deviation from Einstein's theory is ≤ 10-2 with 95% confidence. An explanation of the effect that these divergences have on the CMB power spectrum are discussed, as well as the effect that future 21 cm survey data will have on this study. The last part of this work is a move towards inflation, the early epoch of accelerated expansion undergone by the Universe. Here a parametrisation of the acceleration trajectory is investigated with the aim of measuring the rolling of the inflaton corresponding to the value of the tensor-to-scalar ratio r to be compared with future observations. Considering five ln ε amplitudes and 14 e-foldings, it was found that the posterior distribution of (r,∆Φ) is in very good agreement with Lyth's bound. The analysis included a histogram depiction of the latter result, from which later a minimum constraint on ∆ϕ for each of the bins was found. These outcomes constitute the intermediate step of this project which will be made more accurate by extending it to ~ 50 e-folds, a larger set of cosmological parameters and observational bounds that are restrictive on small scales.

L'organisme Eurocontrol prévoit une forte hausse du trafic aérien européen d'ici l'année 2035. Cette hausse de trafic justifie le développement de nouveaux concepts et outils pour pouvoir assurer les services dus aux usagers de l'espace aérien. La prévision de trajectoires d'avion est au coeur de ces évolutions. Parmi ces outils, les outils de détection et résolution de conflits utilisent les trajectoires prédites pour anticiper les pertes de séparation entre avions et proposer des solutions aux contrôleurs aériens. L'horizon de prédiction utilisé pour cette application est de l'ordre de dix à vingt minutes. Parmi les algorithmes réalisant une détection et résolution de conflits, certains sont mis en œuvre au sol, obligeant ainsi les prédictions à être calculées en n'utilisant que les informations disponibles dans les systèmes sols. Dans ces systèmes, la masse des avions ainsi que les profils de vitesse ou de poussée des moteurs ne sont pas connus. Ainsi, le calcul d'une trajectoire prédite avec un modèle physique se fait en utilisant des valeurs de référence pour les paramètres inconnus. Dans ce cadre, nous nous intéressons à la phase de montée pour laquelle ces paramètres influent grandement sur la trajectoire de l'avion. Ce travail s'appuie sur le modèle physique BADA développé et maintenu par Eurocontrol. Ce modèle physique modélise, entre autres, les performances des avions. Il fournit également des valeurs de référence pour les paramètres inconnus comme la masse de l'avion, son profil de vitesse en montée, ou la commande de poussée des moteurs. Ce modèle, largement utilisé dans le monde entier, est particulièrement imprécis pour la phase de montée, car les valeurs réelles de ces paramètres sont parfois très éloignées des valeurs de référence. Dans cette thèse, nous proposons soit d'estimer directement certains paramètres, comme la masse, à partir des points passés de la trajectoire, soit d'utiliser des méthodes d'apprentissage supervisé afin d'apprendre, à partir d'exemples, des modèles prédisant les valeurs des paramètres manquants (masse, loi de poussée, vitesses cibles). Ces différentes méthodes sont testées sur des données radar Mode-C et Mode-S sur plusieurs types d'avions. Les prédictions obtenues avec ces méthodes sont comparées à celles obtenues avec les paramètres de référence. Elles sont également comparées avec les prédictions obtenues par des méthodes de régression prédisant directement l'altitude de l'avion plutôt que les paramètres du modèle physique. Nos méthodes permettent de réduire, suivant le type de l'avion, de 50 % à 85 % par rapport à la méthode BADA de référence, la racine de l'erreur quadratique moyenne sur l'altitude prédite à un horizon de dix minutes. / The Eurocontrol organization forecasts a strong increase of the European air traffic till the year 2035. This growth justifies the development of new concepts and tools in order to ensure services to airspace users. Trajectory prediction is at the core of these developments. Among these tools, conflict detection and resolution tools use trajectory predictions to anticipate losses of separation between aircraft and propose solutions to air traffic controllers. For such applications, the time horizon of the prediction is about ten to twenty minutes. Among conflict detection and resolution algorithms, some are operated in ground-based systems. The trajectory predictions must then be computed using only the information that is available to ground systems. In these systems, the mass, the speed profile and the thrust setting are unknown. Thus, using a physical model, the trajectory predictions are computed using reference values for unknown parameters. In this context, we are focusing on the climb phase. In this phase these unknown parameters have a great influence on the aircraft trajectory. This work relies on a physical model of the aircraft performances : BADA, developed and maintained by Eurocontrol. It also provides reference values for unknown parameters such as the mass, the speed profile and the thrust setting. This widely used model is particularly inaccurate for the climb phase as the actual values for the unknown parameters might be very different from the reference values. In this thesis, we propose to estimate directly the mass, an unknown parameter, using a physical model and past points of the trajectory. We also use supervised learning methods in order to learn, from examples, some models predicting the unknown parameters (mass, speed profile and thrust setting). These different approaches are tested using Mode-C Radar data and Mode-S Radar data with different aircraft types. The obtained predictions are compared with the ones obtained with the BADA reference values. These predictions are also compared with predictions obtained by directly predicting the future altitude instead of the unknown parameters of the physical model. These methods, depending on the aircraft type, reduces the root mean square error on the predicted altitude at a 10 min horizon by 50 % to 85 % when compared to the root mean square error obtained using BADA with the reference values.