976 resultados para Atmospheric Electric Parameters


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In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

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We have investigated the influence of electrode material and crystallographic structure on electron transfer and biofilm formation of Geobacter sulfurreducens. Single-crystal gold - Au(110), Au(111), Au(210) - and platinum - Pt(100), Pt(110), Pt(111), Pt(210) - electrodes were tested and compared to graphite rods. G. sulfurreducens electrochemically interacts with all these materials with different attachment kinetics and final current production, although redox species involved in the electron transfer to the anode are virtually the same in all cases. Initial bacterial colonization was fastest on graphite up to the monolayer level, whereas gold electrodes led to higher final current densities. Crystal geometry showed to have an important influence, with Au(210) sustaining a current density of up to 1442 (± 101) μA cm- 2 at the steady state, over Au(111) with 961 (± 94) μA cm- 2 and Au(110) with 944 (± 89) μA cm- 2. On the other hand, the platinum electrodes displayed the lowest performances, including Pt(210). Our results indicate that both crystal geometry and electrode material are key parameters for the efficient interaction of bacteria with the substrate and should be considered for the design of novel materials and microbial devices to optimize energy production.

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The middle Miocene Climatic Optimum (17-15 Ma; MCO) is a period of global warmth and relatively high CO2 and is thought to be associated with a significant retreat of the Antarctic Ice Sheet (AIS). We present here a new planktic foraminiferal d11B record from 16.6 to 11.8 Ma from two deep ocean sites currently in equilibrium with the atmosphere with respect to CO2. These new data demonstrate that the evolution of global climate during the middle Miocene (as reflected by changes in the cyrosphere) was well correlated to variations in the concentration of atmospheric CO2. What is more, within our sampling resolution (~1 sample per 300 kyr) there is no evidence of hysteresis in the response of ice volume to CO2 forcing during the middle Miocene, contrary to what is understood about the Antarctic Ice Sheet from ice sheet modelling studies. In agreement with previous data, we show that absolute levels of CO2 during the MCO were relatively modest (350-400 ppm) and levels either side of the MCO are similar or lower than the pre-industrial (200-260 ppm). These new data imply the presence of either a very dynamic AIS at relatively low CO2 during the middle Miocene or the advance and retreat of significant northern hemisphere ice. Recent drilling on the Antarctic margin and shore based studies indicate significant retreat and advance beyond the modern limits of the AIS did occur during the middle Miocene, but the complete loss of the AIS was unlikely. Consequently, it seems that ice volume and climate variations during the middle Miocene probably involved a more dynamic AIS than the modern but also some component of land-based ice in the northern hemisphere.

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Mode of access: Internet.

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"Project No. 1426, Task No. 142612."

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A study of vapour-liquid equilibria is presented together with current developments. The theory of vapour-liquid equilibria is discussed. Both experimental and prediction methods for obtaining vapour-liquid equilibria data are critically reviewed. The development of a new family of equilibrium stills to measure experimental VLE data from sub-atmosphere to 35 bar pressure is described. Existing experimental techniques are reviewed, to highlight the needs for these new apparati and their major attributes. Details are provided of how apparatus may be further improved and how computer control may be implemented. To provide a rigorous test of the apparatus the stills have been commissioned using acetic acid-water mixture at one atmosphere pressure. A Barker-type consistency test computer program, which allows for association in both phases has been applied to the data generated and clearly shows that the stills produce data of a very high quality. Two high quality data sets, for the mixture acetone-chloroform, have been generated at one atmosphere and 64.3oC. These data are used to investigate the ability of the new novel technique, based on molecular parameters, to predict VLE data for highly polar mixtures. Eight, vapour-liquid equilibrium data sets have been produced for the cyclohexane-ethanol mixture at one atmosphere, 2, 4, 6, 8 and 11 bar, 90.9oC and 132.8oC. These data sets have been tested for thermodynamic consistency using a Barker-type fitting package and shown to be of high quality. The data have been used to investigate the dependence of UNIQUAC parameters with temperature. The data have in addition been used to compare directly the performance of the predictive methods - Original UNIFAC, a modified version of UNIFAC, and the new novel technique, based on molecular parameters developed from generalised London's potential (GLP) theory.

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This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

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This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

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A high frequency physical phase variable electric machine model was developed using FE analysis. The model was implemented in a machine drive environment with hardware-in-the-loop. The novelty of the proposed model is that it is derived based on the actual geometrical and other physical information of the motor, considering each individual turn in the winding. This is the first attempt to develop such a model to obtain high frequency machine parameters without resorting to expensive experimental procedures currently in use. The model was used in a dynamic simulation environment to predict inverter-motor interaction. This includes motor terminal overvoltage, current spikes, as well as switching effects. In addition, a complete drive model was developed for electromagnetic interference (EMI) analysis and evaluation. This consists of the lumped parameter models of different system components, such as cable, inverter, and motor. The lumped parameter models enable faster simulations. The results obtained were verified by experimental measurements and excellent agreements were obtained. A change in the winding arrangement and its influence on the motor high frequency behavior has also been investigated. This was shown to have a little effect on the parameter values and in the motor high frequency behavior for equal number of turns. An accurate prediction of overvoltage and EMI in the design stages of the drive system would reduce the time required for the design modifications as well as for the evaluation of EMC compliance issues. The model can be utilized in the design optimization and insulation selection for motors. Use of this procedure could prove economical, as it would help designers develop and test new motor designs for the evaluation of operational impacts in various motor drive applications.

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Sexually-selected communication signals can be used by competing males to settle contests without incurring the costs of fighting. The ability to dynamically regulate the signal in a context-dependent manner can further minimize the costs of male aggressive interactions. Such is the case in the gymnotiform fish Brachyhypopomus gauderio, which, by coupling its electric organ discharge (EOD) waveform to endocrine systems with circadian, seasonal, and behavioral drivers, can regulate its signal to derive the greatest reproductive benefit. My dissertation research examined the functional role of the EOD plasticity observed in male B. gauderio and the physiological mechanisms that regulate the enhanced male EOD. To evaluate whether social competition drives the EOD changes observed during male-male interactions, I manipulated the number of males in breeding groups to create conditions that exemplified low and high competition and measured their EOD and steroid hormone levels. My results showed that social competition drives the enhancement of the EOD amplitude of male B. gauderio. In addition, changes in the EOD of males due to changes in their social environment were paralleled by changes in the levels of androgens and cortisol. I also examined the relationship between body size asymmetry, EOD waveform parameters, and aggressive physical behaviors during male-male interactions in B. gauderio, in order to understand more fully the role of EOD waveforms as reliable signals. While body size was the best determinant of dominance in male B. gauderio, EOD amplitude reliably predicted body condition, a composite of length and weight, for fish in good body condition. To further characterize the mechanisms underlying the relationship between male-male interactions and EOD plasticity, I identified the expression of the serotonin receptor 1A, a key player in the regulation of aggressive behavior, in the brains of B. gauderio. I also identified putative regulatory regions in this receptor in B. gauderio and other teleost fish, highlighting the presence of additional plasticity. In conclusion, male-male competition seems to be a strong selective driver in the evolution of the male EOD plasticity in B. gauderio via the regulatory control of steroid hormones and the serotonergic system.

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Simulations suggest that photomixing in resonant laser-assisted field emission could be used to generate and detect signals from DC to 100 THz. It is the objective of this research to develop a system to efficiently couple the microwave signals generated on an emitting tip by optical mixing. Four different methods for coupling are studied. Tapered Goubau line is found to be the most suitable. Goubau line theory is reviewed, and programs are written to determine loss on the line. From this, Goubau tapers are designed that have a 1:100 bandwidth. These tapers are finally simulated using finite difference time domain, to find the optimum design parameters. Tapered Goubau line is an effective method for coupling power from the field emitting tip. It has large bandwidth, and acceptable loss. Another important consideration is that it is the easiest to manufacture of the four possibilities studied, an important quality for any prototype.

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Sexually-selected communication signals can be used by competing males to settle contests without incurring the costs of fighting. The ability to dynamically regulate the signal in a context-dependent manner can further minimize the costs of male aggressive interactions. Such is the case in the gymnotiform fish Brachyhypopomus gauderio, which, by coupling its electric organ discharge (EOD) waveform to endocrine systems with circadian, seasonal, and behavioral drivers, can regulate its signal to derive the greatest reproductive benefit. My dissertation research examined the functional role of the EOD plasticity observed in male B. gauderio and the physiological mechanisms that regulate the enhanced male EOD. To evaluate whether social competition drives the EOD changes observed during male-male interactions, I manipulated the number of males in breeding groups to create conditions that exemplified low and high competition and measured their EOD and steroid hormone levels. My results showed that social competition drives the enhancement of the EOD amplitude of male B. gauderio. In addition, changes in the EOD of males due to changes in their social environment were paralleled by changes in the levels of androgens and cortisol. I also examined the relationship between body size asymmetry, EOD waveform parameters, and aggressive physical behaviors during male-male interactions in B. gauderio, in order to understand more fully the role of EOD waveforms as reliable signals. While body size was the best determinant of dominance in male B. gauderio, EOD amplitude reliably predicted body condition, a composite of length and weight, for fish in good body condition. To further characterize the mechanisms underlying the relationship between male-male interactions and EOD plasticity, I identified the expression of the serotonin receptor 1A, a key player in the regulation of aggressive behavior, in the brains of B. gauderio. I also identified putative regulatory regions in this receptor in B. gauderio and other teleost fish, highlighting the presence of additional plasticity. In conclusion, male-male competition seems to be a strong selective driver in the evolution of the male EOD plasticity in B. gauderio via the regulatory control of steroid hormones and the serotonergic system.

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An accurate knowledge of the fluorescence yield and its dependence on atmospheric properties such as pressure, temperature or humidity is essential to obtain a reliable measurement of the primary energy of cosmic rays in experiments using the fluorescence technique. In this work, several sets of fluorescence yield data (i.e. absolute value and quenching parameters) are described and compared. A simple procedure to study the effect of the assumed fluorescence yield on the reconstructed shower parameters (energy and shower maximum depth) as a function of the primary features has been developed. As an application, the effect of water vapor and temperature dependence of the collisional cross section on the fluorescence yield and its impact on the reconstruction of primary energy and shower maximum depth has been studied. Published by Elsevier B.V.

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The aerosols in the atmosphere play major role in the radiation balance of the Earthatmosphere system. Direct and indirect impact of aerosols on the weather and climate still remains as a topic to be investigated in detail. The effect of aerosols on the radiation budget and thereby circulation pattern is important and requires further study. A detailed analysis of the aerosol properties, their variability and meteorological processes that affect the aerosol properties and distribution over the Indian region is performed in the thesis. The doctoral thesis entitled “Characteristics of aerosols over the Indian region and their variability associated with atmospheric conditions” contains 7 chapters. This thesis presents results on the analysis on the distribution (spatial and temporal) and characteristics of the aerosols over the Indian region and adjoining seas. Regional and stationwise data were analysed and methods such as modeling and statistical analysis are implemented to understand the aerosol properties, classification and transportation. Chapter-1 presents a brief introduction on the aerosols, their measurement techniques, impact of aerosols on the atmospheric radiation budget, climatic and geographic features of the study area and the literature review on the previous studies. It provides a basic understanding in the field of study and objective of the thesis. Definition of the aerosols, their sources/sinks and classification of the particles according to optical and microphysical properties are described. Different measurement techniques such as sampling and remote sensing methods are explained in detail. Physical parameters used to describe aerosol properties and effect of aerosols on the radiation distribution are also discussed. The chapter also explains the objectives of the thesis and description of climatic features of the study area.

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Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.