International Journal of Engineering
Volume:21 Issue: 3, Sep 2008

Using finite element nonlinear analysis, the dynamic soil pressure on perimeter retainingwalls of structures is investigated. Nonlinear Drucker Prager failure criterion is used to model the soilbehavior in the near field. The far field soil and the middle structure are assumed to behave as linearelastic materials. The soil-wall interface behavior is modeled incorporating nonlinear interfaceelements. The internal friction angle of the soil is found to be an important factor in the dynamiclateral pressure that has been neglected in the previous investigations. Furthermore, a new diagram isproposed to determine lateral seismic soil thrust on rigid walls.

In this paper mathematical formulation for buckling analysis of a column and vibrationanalysis of a beam is presented. The beam and the column is assumed to be non-uniform and cracked.Using calculus of variations, the problem is expressed as an optimization problem. A technique ofoptimization is used for analysis of buckling load. Considering the similarity between the governingequation for buckling and free vibration, the fundamental frequency and mode shape of the beam iscomputed with the same method. Several examples are solved and the results are compared with othermethods, as a result an excellent agreement was obtained.

Several approaches have been introduced in literature for active noise control (ANC)systems. Since Filtered-x-Least Mean Square (FxLMS) algorithm appears to be the best choice as acontroller filter. Researchers tend to improve performance of ANC systems by enhancing andmodifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANCapplications an online secondary path modelling method using a white noise as a training signal isrequired to ensure convergence of the system. This paper also proposes a new approach for onlinesecondary path modelling in feedfoward ANC systems. The proposed algorithm is designed in a waythat the injection of white noise is stopped at the optimum point, when the modelling accuracy issufficient. In this approach, a sudden change in secondary path during the operation makes thealgorithm to reactivate injection of the white noise to adjust the secondary path estimation. Benefitingnew version of the FxLMS algorithm and not a continual injection of white noise during systemoperation makes the proposed system more desirable, also improves the noise attenuation andconvergence rate. Comparative simulation results shown in this paper indicate effectiveness of theproposed approach.

This paper proposes a novel method based on pulse width modulation techniques toreduce and control the common-mode voltage in three-phase multilevel inverters. Besides controllingthe common-mode voltage, this method is capable of controlling capacitors voltages and load currentswith low switching losses and harmonic contents. In fact, due to the existence of different pulsepatterns and the possibility of choosing the optimum patterns based on the most important criteria, thecontrollability of this method has risen properly. Furthermore, the controller randomly selects one ofthe optimum pulse patterns, which has another advantage of spreading the spectrum contents of theoutput voltage for low electromagnetic interferences and mechanical vibration. This method can beapplied to a three-phase, three-level inverter with the flying capacitor topology. Another advantage ofthis method is that the technique can be applied to more voltage levels without significantly changingthe control algorithm. The simulation results of a five-level inverter in this paper indicate that theproposed technique can be used to implement a multilevel inverter.

RoboCup competition as a great test-bed, has turned to a worldwide popular domains in recent years. The main object of such competitions is to deal with complex behavior of systems whichconsist of multiple autonomous agents. The rich experience of human soccer player can be used as a valuable reference for a robot soccer player. However, because of the differences between real and simulated soccer world, it needs to fit such precious transcendental knowledge to use in the simulated soccer game. On the other hand, Reinforcement Learning (RL) as a common method in this domain because of its trial-and-error nature does not have great performance in using transcendental knowledge. Thus, this method is limited to complex multi-agent learning problems. Among various frameworks of intelligences, in general, Artificial Neural Networks (ANN) and specially Kohonen neural networks with its feed-forward architecture and its ability in discovering any relationships of interest that may exist in the input data may be considered as a powerful tool in clustering. This paper puts forward an unsupervised learning method based on Kohonen network to create a powerful Tactics layer in decision-making section for an attacker agent. The approach presented in this paper is based on the combination of expert’s knowledge and data obtained from the simulated world. This system is applied to the attacker agents of ULA 2006 soccer team. Simulation results revealed that the chosen approach is superior with respect to the other intelligent techniques.

This paper presents a novel, multi-objective model of a parallel machines scheduling problem that minimizes the number of tardy jobs and total completion time of all jobs. In this model, machines are considered as unrelated parallel units with different speeds. In addition, there is some precedence, relating the jobs with non-identical due dates and their ready times. Sequence-dependent setup times embedded in the proposed model may vary in different machines based on their characteristics. This paper proposes a two-level mixed-integer programming for the given problem. By solving the presented model, the associated promising results show the effectiveness of this model for small and medium-sized problems, respectively.

This article will introduce a robust vision system which was implemented on a mobile manipulator. This robot has to find objects and deliver them to pre specified locations. In the first stage, a method which is named color adjacency method was employed. However, this method needs a large amount of memory and the process is very slow on computers with small memories. Therefore since the previous methods, had used statistical method for object detection, the samples for the connectionist were extracted by this method. The obtained neural network is very robust against light changes and can detect objects very quickly. This neural network has the advantage of being extremely simple to implement, and astonishingly quick in practice

The transient motion and the heat transfer of a viscous incompressible flow contained between two vertically eccentric spheres maintained at different temperatures and rotating about a common axis with different angular velocities is numerically considered when the angular velocities are an arbitrary functions of time. The resulting flow pattern, temperature distribution, and heat transfer characteristics are presented for the various cases including exponential and sinusoidal angular velocities. Interesting effect of long delays in heat transfer of large portions of the fluid in the annulus is observed because of the angular velocities of the corresponding spheres. As the eccentricity increases and the gap between the spheres decreases, the coriolis forces and convection heat transfer effect in the narrower portion increase.