939 resultados para ENERGY LEVEL CROSSING


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In the context of ƒ (R) gravity theories, we show that the apparent mass of a neutron star as seen from an observer at infinity is numerically calculable but requires careful matching, first at the star’s edge, between interior and exterior solutions, none of them being totally Schwarzschild-like but presenting instead small oscillations of the curvature scalar R; and second at large radii, where the Newtonian potential is used to identify the mass of the neutron star. We find that for the same equation of state, this mass definition is always larger than its general relativistic counterpart. We exemplify this with quadratic R^2 and Hu-Sawicki-like modifications of the standard General Relativity action. Therefore, the finding of two-solar mass neutron stars basically imposes no constraint on stable ƒ (R) theories. However, star radii are in general smaller than in General Relativity, which can give an observational handle on such classes of models at the astrophysical level. Both larger masses and smaller matter radii are due to much of the apparent effective energy residing in the outer metric for scalar-tensor theories. Finally, because the ƒ (R) neutron star masses can be much larger than General Relativity counterparts, the total energy available for radiating gravitational waves could be of order several solar masses, and thus a merger of these stars constitutes an interesting wave source.

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BACKGROUND:Tackling inequalities in overweight, obesity and related determinants has become a top priority for the European research and policy agendas. Although it has been established that such inequalities accumulate from early childhood onward, they have not been studied extensively in children. The current article discusses the results of an explorative analysis for the identification of inequalities in behaviours and their determinants between groups with high and low socio-economic status. METHODS: This study is part of the Epode for the Promotion of Health Equity (EPHE) evaluation study, the overall aim of which is to assess the impact and sustainability of EPODE methodology to diminish inequalities in childhood obesity and overweight. Seven community-based programmes from different European countries (Belgium, Bulgaria, France, Greece, Portugal, Romania, The Netherlands) participate in the EPHE study. In each of the communities, children aged 6-8 years participated, resulting in a total sample of 1266 children and their families. A parental self-administrated questionnaire was disseminated in order to assess the socio-economic status of the household, selected energy balance-related behaviours (1. fruit and vegetable consumption; 2. soft drink/ fruit juices and water consumption; 3. screen time and 4. sleep duration) of the children and associated family environmental determinants. The Mann-Whitney U test and Pearson's chi-square test were used to test differences between the low and high education groups. The country-specific median was chosen as the cut-off point to determine the educational level, given the different average educational level in every country. RESULTS: Children with mothers of relatively high educational level consumed fruits and vegetables more frequently than their peers of low socio-economic status. The latter group of children had a higher intake of fruit juices and/or soft drinks and had higher screen time. Parental rules and home availability were consistently different between the two socio-economic groups in our study in all countries. However we did not find a common pattern for all behaviours and the variability across the countries was large. CONCLUSIONS: Our findings are indicative of socio-economic inequalities in our samples, although the variability across the countries was large. The effectiveness of interventions aimed at chancing parental rules and behaviour on health inequalities should be studied.

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It is recognized that sedentary behavior (SB) has deleterious effects on numerous health outcomes and it appears that physiological mechanisms underlying these harms are distinct from the ones explaining moderate-to-vigorous physical activity (MVPA) benefits. Sedentary behavior represents a large portion of human’s life and is increasing with technological development. A new current of opinion supports the idea that the manner SB is accumulated plays an important role. This dissertation presents six research studies conducted under the scope of SB. In the methodological area, the first study highlighted the magnitude of potential errors in estimating SB and its patterns from common alternative methods (accelerometer and heart rate monitor) compared to ActivPAL. This study presented the accelerometer as a valid method at a group level. Two studies (2 and 5) were performed in older adults (the most sedentary group in the population) to test the associations for SB patterns with abdominal obesity using accelerometry. The findings showed positive graded associations for prolonged sedentary bouts with abdominal obesity and showed that those who interrupted SB more frequently were less likely to present abdominal obesity. Therefore, public health recommendations regarding breaking up SB more often are expected to be relevant. The associations between sedentary patterns and abdominal obesity were independent of MVPA in older adults. However, the low MVPA in this group makes it unclear whether this independent relationship still exists if highly active persons are analysed. Study 3 inovates by examining the association of SB with body fatness in highly trained athletes and found SB to predict total fat mass and trunk fat mass, independently of age and weekly training time. Study 4 also brings novelty to this research field by quantifying the metabolic and energetic cost of the transition from sitting to standing and then sitting back down (a break), informing about the modest energetic costs (0.32 kcal·min−1). Finally, from a successful multicomponent pilot intervention to reduce and break up SB (study 6), an important behavioral resistance to make more sit/stand transitions despite successfully reducing sitting time (~ 1.85 hours·day-1) was found, which may be relevant to inform future behavioral modification programs. The present work provides observational and experimental evidence on the relation for SB patterns with body composition outcomes and energy regulation that may be relevant for public health interventions.

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Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.

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Feed-in-tariff (FIT) schemes have been widely employed to promote renewable energy deployment. While FITs may be perceived by consumers as an extra cost, renewable energies cause a noticeable price reduction in wholesale electricity markets. We analyse both effects for the case of the Spanish electricity market during 2010. In particular, we examine the level of FITs that makes savings and extra costs to be similar on an hourly basis. Results are obtained for a wide range of renewable generation scenarios. It is found that FITs with null extra costs for consumers are in the range of 50–80 €/MWh. Some of the side-effects of a high penetration of renewable energy in the market are analysed in detail and discussed.

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Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

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Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.

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In a globalized economy, the use of natural resources is determined by the demand of modern production and consumption systems, and by infrastructure development. Sustainable natural resource use will require good governance and management based on sound scientific information, data and indicators. There is a rich literature on natural resource management, yet the national and global scale and macro-economic policy making has been underrepresented. We provide an overview of the scholarly literature on multi-scale governance of natural resources, focusing on the information required by relevant actors from local to global scale. Global natural resource use is largely determined by national, regional, and local policies. We observe that in recent decades, the development of public policies of natural resource use has been fostered by an “inspiration cycle” between the research, policy and statistics community, fostering social learning. Effective natural resource policies require adequate monitoring tools, in particular indicators for the use of materials, energy, land, and water as well as waste and GHG emissions of national economies. We summarize the state-of-the-art of the application of accounting methods and data sources for national material flow accounts and indicators, including territorial and product-life-cycle based approaches. We show how accounts on natural resource use can inform the Sustainable Development Goals (SDGs) and argue that information on natural resource use, and in particular footprint indicators, will be indispensable for a consistent implementation of the SDGs. We recognize that improving the knowledge base for global natural resource use will require further institutional development including at national and international levels, for which we outline options.

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This paper presents an integrated model for an offshore wind energy system taking into consideration a contribution for the marine wave and wind speed with perturbations influences on the power quality of current injected into the electric grid. The paper deals with the simulation of one floating offshore wind turbine equipped with a PMSG and a two-level converter connected to an onshore electric grid. The use of discrete mass modeling is accessed in order to reveal by computing the THD on how the perturbations of the captured energy are attenuated at the electric grid injection point. Two torque actions are considered for the three-mass modeling, the aerodynamic on the flexible part and on the rigid part of the blades. Also, a torque due to the influence of marine waves in deep water is considered. PI fractional-order control supports the control strategy. A comparison between the drive train models is presented.

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This paper is about a PhD thesis and includes the study and analysis of the performance of an onshore wind energy conversion system. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as integer-order controllers, fractional-order controllers, fuzzy logic controllers, adaptive controllers and predictive controllers and the study of a supervisor based on finite state machines is also studied. The controllers are included in the lower level of a hierarchical structure composed by two levels whose objective is to control the electric output power around the rated power. The supervisor included at the higher level is based on finite state machines whose objective is to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the wind energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. The wind energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two mass drive train, a gearbox, a doubly fed induction generator rotor and by a two level converter.

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This paper is on modeling and simulation for an offshore wind system equipped with a semi-submersible floating platform, a wind turbine, a permanent magnet synchronous generator, a multiple point clamped four level or five level full-power converter, a submarine cable and a second order filter. The drive train is modeled by three mass model considering the resistant stiffness torque, structure and tower in deep water due to the moving surface elevation. The system control uses PWM by space vector modulation associated with sliding mode and proportional integral controllers. The electric energy is injected into the electric grid either by an alternated current link or by a direct current link. The model is intend to be a useful tool for unveil the behavior and performance of the offshore wind system, especially for the multiple point clamped full-power converter, under normal operation or under malfunctions.

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An integrated mathematical model for the simulation of an offshore wind system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using multiple point full-power clamped three-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a HVDC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the blades of the wind turbine, tower and generator due to the need to emulate the effects of the wind and the floating motion. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistors of the converter. Finally, a case study is presented to access the system performance.

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The use of renewable energies as a response to the EU targets defined for 2030 Climate Change and Energy has been increasing. Also non-dispatchable and intermittent renewable energies like wind and solar cannot generally match supply and demand, which can also cause some problems in the grid. So, the increased interest in energy storage has evolved and there is nowadays an urgent need for larger energy storage capacity. Compressed Air Energy Storage (CAES) is a proven technology for storing large quantities of electrical energy in the form of high-pressure air for later use when electricity is needed. It exists since the 1970’s and is one of the few energy storage technologies suitable for long duration (tens of hours) and utility scale (hundreds to thousands of MW) applications. It is also one of the most cost-effective solutions for large to small scale storage applications. Compressed Air Energy Storage can be integrated and bring advantages to different levels of the electric system, from the Generation level, to the Transmission and Distribution levels, so in this paper a revisit of CAES is done in order to better understand what and how it can be used for our modern needs of energy storage.

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The main objective of this PhD thesis is to optimize a specific multifunctional maritime structure for harbour protection and energy production, named Overtopping Breakwater for Energy Conversion (OBREC), developed by the team of the University of Campania. This device is provided with a sloping plate followed by a unique reservoir, which is linked with the machine room (where the energy conversion occurs) by means of a pipe passing through the crown wall, provided with a parapet on top of it. Therefore, the potential energy of the overtopping waves, collected inside the reservoir located above the still water level, is then converted by means of low – head turbines. In order to improve the understanding of the wave – structure interactions with OBREC, several methodologies have been used and combined together: i. analysis of recent experimental campaigns on wave overtopping discharges and pressures at the crown wall on small – scale OBREC cross sections, carried out in other laboratories by the team of the University of Campania; ii. new experiments on cross sections similar to the OBREC device, planned and carried out in the hydraulic lab at the University of Bologna in the framework of this PhD work; iii. numerical modelling with a 1 – phase incompressible fluid model IH – 2VOF, developed by the University of Cantabria, and with a 2 – phase incompressible fluid model OpenFOAM, both available from the literature; iv. numerical modelling with a new 2 – phase compressible fluid model developed in the OpenFOAM environment within this PhD work; v. analysis of the data gained from the monitoring of the OBREC prototype installation.

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In the last decades the automotive sector has seen a technological revolution, due mainly to the more restrictive regulation, the newly introduced technologies and, as last, to the poor resources of fossil fuels remaining on Earth. Promising solution in vehicles’ propulsion are represented by alternative architectures and energy sources, for example fuel-cells and pure electric vehicles. The automotive transition to new and green vehicles is passing through the development of hybrid vehicles, that usually combine positive aspects of each technology. To fully exploit the powerful of hybrid vehicles, however, it is important to manage the powertrain’s degrees of freedom in the smartest way possible, otherwise hybridization would be worthless. To this aim, this dissertation is focused on the development of energy management strategies and predictive control functions. Such algorithms have the goal of increasing the powertrain overall efficiency and contextually increasing the driver safety. Such control algorithms have been applied to an axle-split Plug-in Hybrid Electric Vehicle with a complex architecture that allows more than one driving modes, including the pure electric one. The different energy management strategies investigated are mainly three: the vehicle baseline heuristic controller, in the following mentioned as rule-based controller, a sub-optimal controller that can include also predictive functionalities, referred to as Equivalent Consumption Minimization Strategy, and a vehicle global optimum control technique, called Dynamic Programming, also including the high-voltage battery thermal management. During this project, different modelling approaches have been applied to the powertrain, including Hardware-in-the-loop, and diverse powertrain high-level controllers have been developed and implemented, increasing at each step their complexity. It has been proven the potential of using sophisticated powertrain control techniques, and that the gainable benefits in terms of fuel economy are largely influenced by the chose energy management strategy, even considering the powerful vehicle investigated.