988 resultados para electric arc simulation
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This work intends to present a newly developed test setup for dynamic out-of-plane loading using underWater Blast Wave Generators (WBWG) as loading source. Underwater blasting operations have been, during the last decades, subject of research and development of maritime blasting operations (including torpedo studies), aquarium tests for the measurement of blasting energy of industrial explosives and confined underwater blast wave generators. WBWG allow a wide range for the produced blast impulse and surface area distribution. It also avoids the generation of high velocity fragments and reduces atmospheric sound wave. A first objective of this work is to study the behavior of masonry infill walls subjected to blast loading. Three different masonry walls are to be studied, namely unreinforced masonry infill walls and two different reinforcement solutions. These solutions have been studied previously for seismic action mitigation. Subsequently, the walls will be simulated using an explicit finite element code for validation and parametric studies. Finally, a tool to help designers to make informed decisions on the use of infills under blast loading will be presented.
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The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.
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A new very high-order finite volume method to solve problems with harmonic and biharmonic operators for one- dimensional geometries is proposed. The main ingredient is polynomial reconstruction based on local interpolations of mean values providing accurate approximations of the solution up to the sixth-order accuracy. First developed with the harmonic operator, an extension for the biharmonic operator is obtained, which allows designing a very high-order finite volume scheme where the solution is obtained by solving a matrix-free problem. An application in elasticity coupling the two operators is presented. We consider a beam subject to a combination of tensile and bending loads, where the main goal is the stress critical point determination for an intramedullary nail.
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There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.
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This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores
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Dissertação de mestrado integrado em Mechanical Engineering
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In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores
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Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)
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Dissertação de mestrado integrado em Civil Engineering
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This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place. Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.
Operation modes for the electric vehicle in smart grids and smart homes : present and proposed modes
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This paper presents the main operation modes for an electric vehicle (EV) battery charger framed in smart grids and smart homes, i.e., are discussed the present-day and are proposed new operation modes that can represent an asset towards EV adoption. Besides the well-known grid to vehicle (G2V) and vehicle to grid (V2G), this paper proposes two new operation modes: Home-to-vehicle (H2V), where the EV battery charger current is controlled according to the current consumption of the electrical appliances of the home (this operation mode is combined with the G2V and V2G); Vehicle-for-grid (V4G), where the EV battery charger is used for compensating current harmonics or reactive power, simultaneously with the G2V and V2G operation modes. The vehicle-to-home (V2H) operation mode, where the EV can operate as a power source in isolated systems or as an off-line uninterruptible power supply to feed priority appliances of the home during power outages of the electrical grid is presented in this paper framed with the other operation modes. These five operation modes were validated through experimental results using a developed 3.6 kW bidirectional EV battery charger prototype, which was specially designed for these operation modes. The paper describes the developed EV battery charger prototype, detailing the power theory and the voltage and current control strategies used in the control system. The paper presents experimental results for the various operation modes, both in steady-state and during transients.
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T. 10, Fasc. 1