952 resultados para Nonlinear Dynamic Response


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Measurement of the dynamic properties of hydrogen and helium under extreme pressures is a key to understanding the physics of planetary interiors. The inelastic scattering signal from statically compressed hydrogen inside diamond anvil cells at 2.8 GPa and 6.4 GPa was measured at the Diamond Light Source synchrotron facility in the UK. The first direct measurement of the local field correction to the Coulomb interactions in degenerate plasmas was obtained from spectral shifts in the scattering data and compared to predictions by the Utsumi-Ichimaru theory for degenerate electron liquids.

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Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

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A conventional way to identify bridge frequencies is utilizing vibration data measured directly from the bridge. A drawback with this approach is that the deployment and maintenance of the vibration sensors are generally costly and time-consuming. One way to cope with the drawback is an indirect approach utilizing vehicle vibrations while the vehicle passes over the bridge. In the indirect approach, however, the vehicle vibration includes the effect of road surface roughness, which makes it difficult to extract the bridge modal properties. One solution may be subtracting signals of two trailers towed by a vehicle to reduce the effect of road surface roughness. A simplified vehicle-bridge interaction model is used in the numerical simulation; the vehicle - trailer and bridge system are modeled as a coupled model. In addition, a laboratory experiment is carried out to verify results of the simulation and examine feasibility of the damage detection by the indirect method.

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The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

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This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

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Transient responses of electrorheological fluids to square-wave electric fields in steady shear are investigated by computational simulation method. The structure responses of the fluids to the field with high frequency are found to be very similar to that to the field with very low frequency or the sudden applied direct current field. The stress rise processes are also similar in both cases and can be described by an exponential expression. The characteristic time tau of the stress response is found to decrease with the increase of the shear rate (gamma) over dot and the area fraction of the particles phi(2). The relation between them can be roughly expressed as tau proportional to(gamma) over dot(-3/4)phi(2)(-3/2). The simulation results are compared with experimental measurements. The aggregation kinetics of the particles in steady shear is also discussed according to these results.

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Ionic polymer conductive network composite (IPCNC) actuators are a class of electroactive polymer composites that exhibit some interesting electromechanical characteristics such as low voltage actuation, large displacements, and benefit from low density and elastic modulus. Thus, these emerging materials have potential applications in biomimetic and biomedical devices. Whereas significant efforts have been directed toward the development of IPMC actuators, the establishment of a proper mathematical model that could effectively predict the actuators' dynamic behavior is still a key challenge. This paper presents development of an effective modeling strategy for dynamic analysis of IPCNC actuators undergoing large bending deformations. The proposed model is composed of two parts, namely electrical and mechanical dynamic models. The electrical model describes the actuator as a resistive-capacitive (RC) transmission line, whereas the mechanical model describes the actuator as a system of rigid links connected by spring-damping elements. The proposed modeling approach is validated by experimental data, and the results are discussed. © 2014 Elsevier B.V. All rights reserved.

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In this paper, the use of differential evolution ( DE), a global search technique inspired by evolutionary theory, to find the parameters that are required to achieve optimum dynamic response of parallel operation of inverters with no interconnection among the controllers is proposed. Basically, in order to reach such a goal, the system is modeled in a certain way that the slopes of P-omega and Q-V curves are the parameters to be tuned. Such parameters, when properly tuned, result in system's eigenvalues located in positions that assure the system's stability and oscillation-free dynamic response with minimum settling time. This paper describes the modeling approach and provides an overview of the motivation for the optimization and a description of the DE technique. Simulation and experimental results are also presented, and they show the viability of the proposed method.

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We develop a model for spiral galaxies based on a nonlinear realization of the Newtonian dynamics starting from the momentum and mass conservations in the phase space. The radial solution exhibits a rotation curve in qualitative accordance with the observational data.