901 resultados para Automobiles - Dynamics - Computer simulation
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Groundwaters and surface waters from an area of treatment of sand for industrial purposes at Analandia municipality, nearly in the center of Sao Paulo State, Brazil, were chemically and isotopically analyzed with two aims: to evaluate if the anthropogenic activities that has taken place for the last 6 years is affecting the quality of the hydrological resources and to relate the hydrogeochemical behaviour of the uranium isotopes 234U and 238U with the pattern of circulation of groundwaters.
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Water waves generated by a solid mass is a complex phenomenon discussed in this paper by numerical and experimental approaches. A model based on shallow water equations with shocks (Saint Venant) has developed. It can reproduce the amplitude and the energy of the wave quite well, but because it consistently generates a hydraulic jump, it is able to reproduce the profile, in the case of high relative thickness of slide, but in the case of small relative thickness it is unable to reproduce the amplitude of the wave. As the momentum conservation is not verified during the phase of wave creation, a second technique based on discharge transfer coefficient α, is introduced at the zone of impact. Numerical tests have been performed and validated this technique from the experimental results of the wave's height obtained in a flume.
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This work presents the application of a scalar finite element formulation for Ex (TE-like) modes in anisotropic planar and channel waveguides with diagonal permittivity tensor, diffused in both transversal directions. This extended formulation considers explicitly both the variations of the refractive index and their spatial derivates inside of each finite element. Dispersion curves for Ex modes in planar and channel waveguides are shown, and the results compared with solutions obtained by other formulations.
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This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.
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The design of a Gilbert Cell Mixer and a low noise amplifier (LNA), using GaAs PHEMT technology is presented. The compatibility is shown for co-integration of both block on the same chip, to form a high performance 1.9 GHz receiver front-end. The designed LNA shows 9.23 dB gain and 2.01 dB noise figure (NF). The mixer is designed to operate at RF=1.9 GHz, LO=2.0 GHz and IF=100 MHz with a gain of 14.3 dB and single sideband noise figure (SSB NF) of 9.6 dB. The mixer presents a bandwith of 8 GHz.
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This article presents the implementation of a distributed system of virtual reality, through the integration of services offered by the CORBA platform (Common Object Request Broker Architecture) and by the environment of development of 3D graphic applications in real time, the WorldToolkit, of Sense8. The developed application for the validation of this integration is that of a virtual city, with an emphasis on its traffic ways, vehicles (movable objects) and buildings (immovable objects). In this virtual world, several users can interact, each one controlling his/her own car. Since the modelling of the application took into consideration the criteria and principles of the Transport Engineering, the aim is to use it in the planning, project and construction of traffic ways for vehicles. The system was structured according to the approach client/server utilizing multicast communication among the participating nodes. The chosen implementation for the CORBA was the Iona's ORBIX software. The performance results obtained are presented and discussed in the end.
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This work presents a new high power factor three-phase rectifier based on a Y-connected differential autotransformer with reduced kVA and 18-pulse input current followed by three DC-DC boost converters. The topology provides a regulated output voltage and natural three-phase input power factor correction. The lowest input current harmonic components are the 17th and the 19th. Three boost converters, with constant input currents and regulated parallel connected output voltages are used to process 4kW each one. Analytical results from Fourier analyses of winding currents and the vector diagram of winding voltages are presented. Simulation results to verify the proposed concept and experimental results are shown in the paper.
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This paper analyzes the thermal storage characteristics of aluminum plates in furnaces during their heating for lamination under two sources of heat: an electrical resistance bank and a combustion process carried out with natural gas. The set of equations to model the furnace under operation with electrical energy, for air as the fluid, is presented. This supports the theoretical analysis for the system under operation with natural gas combustion products. A numerical procedure, using the software ANSYS, is applied to determine the convection heat transfer coefficients for heating by the air flow. Temperatures measured in a plate inside a real furnace are used as parameters to determine these coefficients. Then convection and radiation heat transfer coefficients are determined for the natural gas combustion products. Results are compared, indicating a possible gain of 5.5 h in relation to a 19.5 h period of conventional electrical heating per plate.
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We analyze the average performance of a general class of learning algorithms for the nondeterministic polynomial time complete problem of rule extraction by a binary perceptron. The examples are generated by a rule implemented by a teacher network of similar architecture. A variational approach is used in trying to identify the potential energy that leads to the largest generalization in the thermodynamic limit. We restrict our search to algorithms that always satisfy the binary constraints. A replica symmetric ansatz leads to a learning algorithm which presents a phase transition in violation of an information theoretical bound. Stability analysis shows that this is due to a failure of the replica symmetric ansatz and the first step of replica symmetry breaking (RSB) is studied. The variational method does not determine a unique potential but it allows construction of a class with a unique minimum within each first order valley. Members of this class improve on the performance of Gibbs algorithm but fail to reach the Bayesian limit in the low generalization phase. They even fail to reach the performance of the best binary, an optimal clipping of the barycenter of version space. We find a trade-off between a good low performance and early onset of perfect generalization. Although the RSB may be locally stable we discuss the possibility that it fails to be the correct saddle point globally. ©2000 The American Physical Society.
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Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.
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Relaxed conditions for the stability study of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. These results are also used for the fuzzy regulators design. The nonlinear systems are represented by the fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by LMIs (Linear Matrix Inequalities), that can be solved efficiently by convex programming techniques. The specification of the decay rate, constraints on control input and output are also described by LMIs. Finally, the proposed design method is applied in the control of an inverted pendulum.
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In this paper we describe a scheduler simulator for real-time tasks, RTsim, that can be used as a tool to teach real-time scheduling algorithms. It simulates a variety of preprogrammed scheduling policies for single and multi-processor systems and simple algorithm variants introduced by its user. Using RTsim students can conduct experiments that will allow them to understand the effects of each policy given different load conditions and learn which policy is better for different workloads. We show how to use RTsim as a learning tool and the results achieved with its application on the Real-Time Systems course taught at the B.Sc. on Computer Science at Paulista State University - Unesp - at Rio Preto.
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The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter estimation problems for nonlinear model with unknown-but-bounded errors and uncertainties. This problem can be represented by a typical constrained optimization problem. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.
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A CMOS memory-cell for dynamic storage of analog data and suitable for LVLP applications is proposed. Information is memorized as the gate-voltage of input-transistor of a gain-boosting triode-transconductor. The enhanced output-resistance improves accuracy on reading out the sampled currents. Additionally, a four-quadrant multiplication between the input to regulation-amplifier of the transconductor and the stored voltage is provided. Designing complies with a low-voltage 1.2μm N-well CMOS fabrication process. For a 1.3V-supply, CCELL=3.6pF and sampling interval is 0.25μA≤ ISAMPLE ≤ 0.75μA. The specified retention time is 1.28ms and corresponds to a charge-variation of 1% due to junction leakage @75°C. A range of MR simulations confirm circuit performance. Absolute read-out error is below O.40% while the four-quadrant multiplier nonlinearity, at full-scale is 8.2%. Maximum stand-by consumption is 3.6μW/cell.
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A new topology for a LVLP variable-gain CMOS amplifier is presented. Input- and load-stage are built around triode-transconductors so that voltage-gain is fully defined by a linear relationship involving only device-geometries and biases. Excellent gain-accuracy, temperature-insensitivity; and wide range of programmability, are thus achieved. Moreover, adaptative biasing improves the common-mode voltage stability upon gain-adjusting. As an example, a 0-40dB programmablegain audio-amplifier is designed. Its performance is supported by a range of simulations. For VDD=1.8V and 20dB-nominal gain, one has Av=19.97dB, f3db=770KHz and quiescent dissipation of 378μW. Over temperatures from -25°C to 125°C, the 0. ldB-bandwidth is 52KHz. Dynamic-range is optimized to 57.2dB and 42.6dB for gains of 20dB and 40dB, respectively. THD figures correspond to -60.6dB@Vout= 1Vpp and -79.7dB@Vout= 0.5 Vpp. A nearly constant bandwidth for different gains is also attained.