945 resultados para hydropower system model


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The Community Climate System Model version 3 is used to analyse changes in water mass subduction rates in the South Atlantic Ocean over the 21st century. The model results are first compared to observations over 1950-2000, and shown to be rather good. The subduction rates do not change significantly over the 21st century, but the densities at which water masses form become significantly lighter. The strong westerly winds in this region do not change much, which suggests small changes to the rate at which the Atlantic sector of the Southern Ocean takes up heat and carbon dioxide over the 21st century.

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The paleoclimate version of the National Center for Atmospheric Research Community Climate System Model version 3 (NCAR-CCSM3) is used to analyze changes in the water formation rates in the Atlantic, Pacific, and Indian Oceans for the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) control climate. During the MH, CCSM3 exhibits a north-south asymmetric response of intermediate water subduction changes in the Atlantic Ocean, with a reduction of 2 Sv in the North Atlantic and an increase of 2 Sv in the South Atlantic relative to PI. During the LGM, there is increased formation of intermediate water and a more stagnant deep ocean in the North Pacific. The production of North Atlantic Deep Water (NADW) is significantly weakened. The NADW is replaced in large extent by enhanced Antarctic Intermediate Water (AAIW), Glacial North Atlantic Intermediate Water (GNAIW), and also by an intensified of Antarctic Bottom Water (AABW), with the latter being a response to the enhanced salinity and ice formation around Antarctica. Most of the LGM intermediate/mode water is formed at 27.4 < sigma(theta) < 29.0 kg/m(3), while for the MH and PI most of the subduction transport occurs at 26.5 < sigma(theta) < 27.4 kg/m(3). The simulated LGM Southern Hemisphere winds are more intense by 0.2-0.4 dyne/cm(2). Consequently, increased Ekman transport drives the production of intermediate water (low salinity) at a larger rate and at higher densities when compared to the other climatic periods.

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This study analyzes important aspects of the tropical Atlantic Ocean from simulations of the fourth version of the Community Climate System Model (CCSM4): the mean sea surface temperature (SST) and wind stress, the Atlantic warm pools, the principal modes of SST variability, and the heat budget in the Benguela region. The main goal was to assess the similarities and differences between the CCSM4 simulations and observations. The results indicate that the tropical Atlantic overall is realistic in CCSM4. However, there are still significant biases in the CCSM4 Atlantic SSTs, with a colder tropical North Atlantic and a hotter tropical South Atlantic, that are related to biases in the wind stress. These are also reflected in the Atlantic warm pools in April and September, with its volume greater than in observations in April and smaller than in observations in September. The variability of SSTs in the tropical Atlantic is well represented in CCSM4. However, in the equatorial and tropical South Atlantic regions, CCSM4 has two distinct modes of variability, in contrast to observed behavior. A model heat budget analysis of the Benguela region indicates that the variability of the upper-ocean temperature is dominated by vertical advection, followed by meridional advection.

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The new Community Climate System Model, version 4 (CCSM4), provides a powerful tool to understand and predict the earth's climate system. Several aspects of the Southern Ocean in the CCSM4 are explored, including the surface climatology and interannual variability, simulation of key climate water masses (Antarctic Bottom Water, Subantarctic Mode Water, and Antarctic Intermediate Water), the transport and structure of the Antarctic Circumpolar Current, and interbasin exchange via the Agulhas and Tasman leakages and at the Brazil-Malvinas Confluence. It is found that the CCSM4 has varying degrees of accuracy in the simulation of the climate of the Southern Ocean when compared with observations. This study has identified aspects of the model that warrant further analysis that will result in a more comprehensive understanding of ocean-atmosphere-ice dynamics and interactions that control the earth's climate and its variability.

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A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.

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The lyotropic liquid crystalline quaternary mixture made of potassium laurate (KL), potassium sulphate, 1-undecanol and water was investigated by experimental optical methods (optical microscopy and laser conoscopy). In a particular temperature and relative concentrations range, the three nematic phases (two uniaxial and one biaxial) were identified. The biaxial domain in the temperature/KL concentration surface is larger when compared to other lyotropic mixtures. Moreover, this new mixture gives nematic phases with higher birefringence than similar systems. The behavior of the symmetric tensor order parameter invariants sigma(3) and sigma(2) calculated from the measured optical birefringences supports that the uniaxial-to-biaxial transitions are of second order, described by a mean-field theory.

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This study is aimed at evaluating the sublethal effects of endosulfan (EDS) in juvenile common carp (Cyprinus carpio). For this purpose, fish were exposed for 15 days to the technical EDS (95% pure) diluted in dimethyl sulfoxide (DMSO) 0.1% of the total volume in water solution in a semi-static system at sublethal concentration (1 mu g/L). Subsequently, the liver somatic index (LSI) and factor condition (K) were determined. The total cytocrome P450 (CYP), CYP1A isoform, and the ethoxyresorufin-O-deethylase (EROD) activity were determined from the hepatic microsomal fraction as well as the activity of the oxidative stress enzyme system such as superoxide dismutase (SOD), catalase (CAT), glutathione-S-transferase (GST), glutathione peroxidase (GP(X)), glutathione reductase (GR), and glucose-6-phosphate dehydrogenase (G6PDH). Among the parameters assessed, EDS at the sublethal concentration in subchronic exposure caused significant changes in liver somatic indices as well as induction of the phase I biotransformation system and oxidative stress in juvenile common carp (Cyprinus carpio). Thus, it is seen that the use of biochemical biomarkers of environmental contamination in this study proved to be an extremely important tool for detecting the adverse effects of xenobiotics in the aquatic environment, even at low concentration.

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Organizational intelligence can be seen as a function of the viable structure of an organization. With the integration of the Viable System Model and Soft Systems Methodology (systemic approaches of organizational management) focused on the role of the intelligence function, it is possible to elaborate a model of action with a structured methodology to prospect, select, treat and distribute information to the entire organization that improves the efficacy and efficiency of all processes. This combination of methodologies is called Intelligence Systems Methodology (ISM) whose assumptions and dynamics are delimited in this paper. The ISM is composed of two simultaneous activities: the Active Environmental Mapping and the Stimulated Action Cycle. The elaboration of the formal ISM description opens opportunities for applications of the methodology on real situations, offering a new path for this specific issue of systems thinking: the intelligence systems. Knowledge Management Research & Practice (2012) 10, 141-152. doi:10.1057/kmrp.2011.44

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Nitrogen removal coupled with sulfide oxidation has potential for the treatment of effluents from anaerobic reactors because they contain sulfide, which can be used as an endogenous electron donor for denitrification. This work evaluated the intrinsic kinetics of sulfide-oxidizing autotrophic denitrification via nitrate and nitrite in systems containing attached cells. Differential reactors were fed with nitrified synthetic domestic sewage and different sulfide concentrations. The intrinsic kinetic parameters of nitrogen removal were determined when the mass transfer resistance was negligible. This bioprocess could be described by a half-order kinetic model for biofilms. The half-order kinetic coefficients ranged from 0.425 to 0.658 mg N-1/2 L-1/2 h(-1) for denitrification via nitrite and from 0.190 to 0.609 mg N-1/2 L-1/2 h(-1) for denitrification via nitrate. In this latter, the lower value was due to the use of electrons donated from intermediary sulfur compounds whose formation and subsequent consumption were detected. (C) 2011 Elsevier Ltd. All rights reserved.

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The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

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Self-organisation is increasingly being regarded as an effective approach to tackle modern systems complexity. The self-organisation approach allows the development of systems exhibiting complex dynamics and adapting to environmental perturbations without requiring a complete knowledge of the future surrounding conditions. However, the development of self-organising systems (SOS) is driven by different principles with respect to traditional software engineering. For instance, engineers typically design systems combining smaller elements where the composition rules depend on the reference paradigm, but typically produce predictable results. Conversely, SOS display non-linear dynamics, which can hardly be captured by deterministic models, and, although robust with respect to external perturbations, are quite sensitive to changes on inner working parameters. In this thesis, we describe methodological aspects concerning the early-design stage of SOS built relying on the Multiagent paradigm: in particular, we refer to the A&A metamodel, where MAS are composed by agents and artefacts, i.e. environmental resources. Then, we describe an architectural pattern that has been extracted from a recurrent solution in designing self-organising systems: this pattern is based on a MAS environment formed by artefacts, modelling non-proactive resources, and environmental agents acting on artefacts so as to enable self-organising mechanisms. In this context, we propose a scientific approach for the early design stage of the engineering of self-organising systems: the process is an iterative one and each cycle is articulated in four stages, modelling, simulation, formal verification, and tuning. During the modelling phase we mainly rely on the existence of a self-organising strategy observed in Nature and, hopefully encoded as a design pattern. Simulations of an abstract system model are used to drive design choices until the required quality properties are obtained, thus providing guarantees that the subsequent design steps would lead to a correct implementation. However, system analysis exclusively based on simulation results does not provide sound guarantees for the engineering of complex systems: to this purpose, we envision the application of formal verification techniques, specifically model checking, in order to exactly characterise the system behaviours. During the tuning stage parameters are tweaked in order to meet the target global dynamics and feasibility constraints. In order to evaluate the methodology, we analysed several systems: in this thesis, we only describe three of them, i.e. the most representative ones for each of the three years of PhD course. We analyse each case study using the presented method, and describe the exploited formal tools and techniques.

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The land-atmosphere exchange of atmospheric trace gases is sensitive to meteorological conditions and climate change. It contributes in turn to the atmospheric radiative forcing through its effects on tropospheric chemistry. The interactions between the hydrological cycle and atmospheric processes are intricate and often involve different levels of feedbacks. The Earth system model EMAC is used in this thesis to assess the direct role of the land surface components of the terrestrial hydrological cycle in the emissions, deposition and transport of key trace gases that control tropospheric chemistry. It is also used to examine its indirect role in changing the tropospheric chemical composition through the feedbacks between the atmospheric and the terrestrial branches of the hydrological cycle. Selected features of the hydrological cycle in EMAC are evaluated using observations from different data sources. The interactions between precipitation and the water vapor column, from the atmospheric branch of the hydrological cycle, and evapotranspiration, from its terrestrial branch, are assessed specially for tropical regions. The impacts of changes in the land surface hydrology on surface exchanges and the oxidizing chemistry of the atmosphere are assessed through two sensitivity simulations. In the first, a new parametrization for rainfall interception in the densely vegetated areas in the tropics is implemented, and its effects are assessed. The second study involves the application of a soil moisture forcing that replaces the model calculated soil moisture. Both experiments have a large impact on the local hydrological cycle, dry deposition of soluble and insoluble gases, emissions of isoprene through changes in surface temperature and the Planetary Boundary Layer height. Additionally the soil moisture forcing causes changes in local vertical transport and large-scale circulation. The changes in trace gas exchanges affect the oxidation capacity of the atmosphere through changes in OH, O$_3$, NO$_x$ concentrations.

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Air-sea interactions are a key process in the forcing of the ocean circulation and the climate. Water Mass Formation is a phenomenon related to extreme air-sea exchanges and heavy heat losses by the water column, being capable to transfer water properties from the surface to great depth and constituting a fundamental component of the thermohaline circulation of the ocean. Wind-driven Coastal Upwelling, on the other hand, is capable to induce intense heat gain in the water column, making this phenomenon important for climate change; further, it can have a noticeable influence on many biological pelagic ecosystems mechanisms. To study some of the fundamental characteristics of Water Mass Formation and Coastal Upwelling phenomena in the Mediterranean Sea, physical reanalysis obtained from the Mediterranean Forecating System model have been used for the period ranging from 1987 to 2012. The first chapter of this dissertation gives the basic description of the Mediterranean Sea circulation, the MFS model implementation, and the air-sea interaction physics. In the second chapter, the problem of Water Mass Formation in the Mediterranean Sea is approached, also performing ad-hoc numerical simulations to study heat balance components. The third chapter considers the study of Mediterranean Coastal Upwelling in some particular areas (Sicily, Gulf of Lion, Aegean Sea) of the Mediterranean Basin, together with the introduction of a new Upwelling Index to characterize and predict upwelling features using only surface estimates of air-sea fluxes. Our conclusions are that latent heat flux is the driving air-sea heat balance component in the Water Mass Formation phenomenon, while sensible heat exchanges are fundamental in Coastal Upwelling process. It is shown that our upwelling index is capable to reproduce the vertical velocity patterns in Coastal Upwelling areas. Nondimensional Marshall numbers evaluations for the open-ocean convection process in the Gulf of Lion show that it is a fully turbulent, three-dimensional phenomenon.

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The variability of the Atlantic meridional overturing circulation (AMOC) strength is investigated in control experiments and in transient simulations of up to the last millennium using the low-resolution Community Climate System Model version 3. In the transient simulations the AMOC exhibits enhanced low-frequency variability that is mainly caused by infrequent transitions between two semi-stable circulation states which amount to a 10 percent change of the maximum overturning. One transition is also found in a control experiment, but the time-varying external forcing significantly increases the probability of the occurrence of such events though not having a direct, linear impact on the AMOC. The transition from a high to a low AMOC state starts with a reduction of the convection in the Labrador and Irminger Seas and goes along with a changed barotropic circulation of both gyres in the North Atlantic and a gradual strengthening of the convection in the Greenland-Iceland-Norwegian (GIN) Seas. In contrast, the transition from a weak to a strong overturning is induced by decreased mixing in the GIN Seas. As a consequence of the transition, regional sea surface temperature (SST) anomalies are found in the midlatitude North Atlantic and in the convection regions with an amplitude of up to 3 K. The atmospheric response to the SST forcing associated with the transition indicates a significant impact on the Scandinavian surface air temperature (SAT) in the order of 1 K. Thus, the changes of the ocean circulation make a major contribution to the Scandinavian SAT variability in the last millennium.

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In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.