Computational Methods in Engineering

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Stator flux oriented vector control of induction motor (IM) drives for speed sensorless control has several advantages. But the application of a pure integrator for the flux estimation is difficult due to the presence of measurement noise and dc offset. To overcome these problems, some have used a programmable cascaded low pass filter (PCLPF). In this paper, it is shown that some problems still exist and some new problems arise from this approach. In order to solve these problems, a novel compensation method is proposed. In this scheme, the dc offset is detected and subtracted from the estimated flux along d and q axes. The simulation results show that it works well in the low speed region as well as in the transient state. The oscillation of the torque and the estimated flux are also reduced notably when the torque reference changes rapidly.

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The rapid growth of space utilization requires extensive construction, and maintenance of space structures and satellites in orbit. This will, in turn, substantiate application of robotic systems in space. In this paper, a near-minimum-time optimal control law is developed for a rigid space platform with flexible links during an orientating maneuver with large angle of rotation. The time optimal control solution for the rigid-body mode is obtained as a bang-bang function and applied to the flexible system after smoothening the control inputs to avoid stimulation of the flexible modes. This will also reflect practical limitations in exerting bang-bang actuator forces/torques, due to delays and non-zero time constants of existing actuation elements. The smoothness of the input command is obtained by reshaping its profile based on consideration of additional first-order and second-order derivative constraints. The platform is modeled as a linear undamped elastic system that yields an appropriate model for the analysis of planar rotational maneuvers. The developed control law is applied on a given satellite during a slewing maneuver. The simulation results show that the modified realistic optimal input compared to the bang-bang solution agrees well with the practical limitations and also alleviates the vibrating motion of the flexible appendage, which reveals the merits of the new control law developed here.

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This paper presents a method based on neural networks to detect broken rotor bars and end rings in squirrel cage induction motors. In the first part, detection methods are reviewed and traditional methods of fault detection as well as dynamic model of induction motors are introduced using the winding function method. In this method, all stator and rotor bars are considered independently in order to check the performance of the motor for any faults in the parts. Then the frequency spectrum of current signals is derived using the Fourier transform and analyzed under various conditions. In the second part of the paper, an analytical discussion of the theoretical principles is presented to arrive at a simple algorithm for fault detection based on neural networks. The neural network has been trained using the information from a 1.1 KW induction motor. Finally, the system is tested with different values of load torque and is found capable of working on-line to detect all normal and ill-performing conditions.

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In spite of the fact that the effect of earthquake on earth dams has been widely studied during the past decades, the complicated behavior of such earth structures against different seismological characteristics is still unknown. Such ambiguities necessitate more accurate studies using more comprehensive computation tools to achieve new results describing the behavior of such structures subjected to earthquake loading. In the present study, the simple soil model of elastic, perfectly plastic (based on the Mohr-Coulomb criterion), and Rayleigh damping criterion have been adopted for the soil. First, the numerical model employed was verified by dynamic analysis of real cases such as “Long Valley” and “santa Felecia” earth dams. The computational results were then compared with real recorded data or with those reported by other researchers. In addition to evaluating seismic stability of earth dams, their seismic stability was verified using pseudo-static analyses. Therefore, the “Carsington” dam was analyzed to verify the results of pseudo-static analyses and to check the results of FLAC software in calculating the pseudo-static factor of safety. The values of calculated factors of safety in the present study are in good agreement with the published results in the literature. Furthermore, the failure behavior revealed in the analysis shows the ability of FLAC software in defining the failure surface. In the main part of the analyses, a parametric study was conducted for different selected conditions and specially the effect of dam height and the optimum size of crest width were investigated. The results are presented in relevant diagrams.

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With respect to the great application of pipes conveying fluid in civil engineering, presenting a mathematical model for their stability analysis is essential. For this purpose, a concrete pipe, reinforced by iron oxide (Fe₂O₃) nanoparticles, conveying fluid  is considered. The goal of this study is to investigate the structural stability to show the effects of the inside fluid and the nanoparticles. The structure was modeled by a cylindrical shell and using Reddy theory. To obtain the force induced by the inside fluid, the Navier-Stokes equation was used. To assume the effect of the nanoparticles in the pipe, the Mori-Tanaka model was utilized so that the effects of agglomeration of nanoparticles could be considered. Finally, by applying energy method and the Hamilton's principle, the governing equations were derived. For the stability analysis of the structure, differential quadrature method (DQM) was proposed and the effects of different parameters such as volume fraction of the nanoparticles and agglomeration of the nanoparticles inside fluid and geometrical parameters were investigated. The results showed that the existence of the nanoparticles as the reinforcement for the pipe led to the delay in the pipe instability.