984 resultados para interface dynamics


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We present an educational software addressed to the students of optical communication courses, for a simple visualization of the basic dynamic processes of semiconductor lasers. The graphic interface allows the user to choose the laser and the modulation parameters and it plots the laser power output and instantaneous frequency versus time. Additionally, the optical frequency variations are numerically shifted into the audible frequency range in order to produce a sound wave from the computer loudspeakers. Using the proposed software, the student can simultaneously see and hear how the laser intensity and frequency change, depending on the modulation and device parameters.

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The first steps towards developing a continuum-molecular coupled simulations techniques are presented, for the purpose of computing macroscopic systems of confined fluids. The idea is to compute the interface wall-fluid by Molecular Dynamics simulations, where Lennard-Jones potential (and others) have been employed for the molecular interactions, so the usual non slip boundary condition is not specified. Instead, a shear rate can be imposed at the wall, which allows to obtain the properties of the wall material by means of an iterative method. The remaining fluid region will be computed by a spectral hp method. We present MD simulations of a Couette flow, and the results of the developed boundary conditions from the wall fluid interaction.

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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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Escoamentos bifásicos estão presentes em diversos processos naturais e industriais, como na indústria de petróleo. Podem apresentar-se em diferentes configurações topológicas, ou, padrões de escoamento, entre eles o escoamento estratificado ondulado e o estratificado com mistura na interface. Os escoamentos bifásicos estratificados óleo-água têm sido utilizados como uma forma conveniente de evitar a formação de emulsões de água em óleo em oleodutos e possuem uma ocorrência comum em poços de petróleo direcionais. Quando a onda interfacial ultrapassa determinado limite geométrico e cinemático, surge o fenômeno do entranhamento de gotas, representado por misturas entre as fases junto à interface que promovem um aumento na queda de pressão. Modelos têm sido apresentados pela literatura na tentativa de descrever o fenômeno do entranhamento de gotas. Neste trabalho é apresentada uma nova proposta de modelagem matemática unidimensional para o entranhamento de gotas com o objetivo de melhorar a previsão dos parâmetros envolvidos, em especial, da fração volumétrica de óleo e da queda de pressão bifásica. Também foi utilizada simulação numérica computacional, CFD (Computational Fluid Dynamics), com o uso de software comercial para obtenção dos valores dos parâmetros do escoamento estratificado ondulado óleo-água (fração volumétrica de óleo, queda de pressão, amplitude e comprimento da onda interfacial). Os resultados da modelagem fenomenológica para entranhamento e os de CFD foram comparados com bancos de dados experimentais. Os resultados em CFD mostram concordância com os resultados experimentais, tanto na análise qualitativa das propriedades geométricas das ondas interfaciais, quanto na comparação direta com os dados para fração volumétrica e queda de pressão. Os resultados numéricos da modelagem fenomenológica para fatores de entranhamento apresentam boa concordância com dados da literatura.

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ABSTRACT Convergent extension is a highly conserved process among mammals, in which the tissue narrows in one axis, and extends across another. Tissue elongation is directed by the regulation of cell interface behaviors, which guides cell intercalation and rosette formation. Rosette formation occurs through the contraction of vertically oriented cell interfaces, and the subsequent elongation of new horizontal interfaces. It has been shown that actomyosin-generated tension functions to direct rosette formation. In this thesis, I have tested the function of regulators of F-actin networks, as well as endocytic and exocytic mechanisms, to identify new components that control interface behaviors and cell shape. I have performed a screen of F-actin regulators and nucleators, and pinpointed the specific actin nucleator dPod-1 as a candidate protein that is localized to vertical interfaces during tissue elongation. Furthermore, I have probed the function of endocytosis using the Shibire mutation, and demonstrated that endocytosis is required for vertical interface shrinking. Finally, I have used mutations in components of the Exocyst Complex and the associated protein RalA to inhibit exocytic mechanisms, in order to address their function in directing cell and tissue morphologies.

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We quantify the rate and efficiency of picosecond electron transfer (ET) from PbS nanocrystals, grown by successive ionic layer adsorption and reaction (SILAR), into a mesoporous SnO2 support. Successive SILAR deposition steps allow for stoichiometry- and size-variation of the QDs, characterized using transmission electron microscopy. Whereas for sulfur-rich (p-type) QD surfaces substantial electron trapping at the QD surface occurs, for lead-rich (n-type) QD surfaces, the QD trapping channel is suppressed and the ET efficiency is boosted. The ET efficiency increase achieved by lead-rich QD surfaces is found to be QD-size dependent, increasing linearly with QD surface area. On the other hand, ET rates are found to be independent of both QD size and surface stoichiometry, suggesting that the donor–acceptor energetics (constituting the driving force for ET) are fixed due to Fermi level pinning at the QD/oxide interface. Implications of our results for QD-sensitized solar cell design are discussed.