ESTEGHLAL
Year:2008 | Volume:27 | Issue:1|Papers Count:10

This paper tries to estimate the capital investment required for the fixed-telephony network switching equipment as demanded by the fourth national development plan. As a first step, the Cobb-Douglas model is used as a successful demand forecasting model to estimate the demand over the target years. Then, an architectural plan is developed for the fixed-telephony switching network that takes into account the expansion of the existing exchanges as well as the addition of new ones. The number of the required ports in local exchanges, the intercity traffic (including cell phone subscribers), and the required trunks in transit exchanges are then estimated. Two scenarios are used to estimate the investment needed: expanding legacy network (circuit-based), and NGN adoption (a combination of circuit and packet-based networks). Finally, conventional pricelists from different local and foreign suppliers are used to arrive at two total investment estimates: 6,013 billion Rials and 6330 billion Rials for the two mentioned scenarios, respectively.

In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like the GLRT method). In the second detector, the averaged likelihood ratio is calculated by integrating out the unknown parameters (like the AALR method). Thanks to the numerical nature of these methods, they can be applied to many detection problems which do not have analytical solutions. Simulation results show that both the proposed detectors and the GLRT have approximately the same performance in problems to which the GLRT can be applied. On the other hand, the proposed detectors can be used in many cases for which either no ML estimate of unknown parameters exists or their prior distribution is known.

This paper presents a nonlinear mixed-integer programming model to minimize the stoppage cost of mixed-model assembly lines. Nowadays, most manufacturing firms employ this type of line due to the increasing varieties of products in their attempts to quickly respond to diversified customer demands. Advancement of new technologies, competitiveness, diversification of products, and large customer demand have encouraged practitioners to use different methods of improving production lines. Minimizing line stoppage is regarded as a main factor in determining the sequence of processing products. Line stoppage results in idleness of operators and machines, reduced throughput, increased overhead costs, and decreased overall productivity. Due to the complexity of the model proposed, which belongs to a class of NP-hard problems, a meta-heuristic method based on a genetic algorithm (GA) is proposed to obtain near-optimal solutions in reasonable time, especially for large-scale problems. To show the efficiency of the proposed GA, the computational results are compared with those obtained by the Lingo software.

In this paper, an elastoplastic constitutive model is presented for predicting sandy soil behavior under monotonic and cyclic loadings. The model is based on the CJS3 model that takes into account deviatoric and isotropic mechanisms of plasticity. The flow rule in deviatoric mechanism is non-associated and a kinematic hardening law controls the evolution of the yield surface. In the present study, the critical state surface and history surface separating the virgin and cyclic states in the stress space are defined. Hardening modulus and stress-dilatancy law for monotonic and cyclic loadings are effectively modified. Taking the hardening modulus as a function of deviatoric and volumetric plastic strain, the model will be capable of predicting sand behavior once the history surface and stress reversal are defined. All model parameters have clear physical meanings and can be determined simply from laboratory tests. The results of homogeneous tests on Hostun sand are used to validate the model. The results of validation indicate the capability of the proposed model.

In recent years, many different plans have been considered to use the nuclear energy gained from inertial confinement fusion (ICF) as attempts to obtain high energy efficiencies. In conventional ICF methods, a small amount (about mg) of the deuterium–tritium compound is confined in a small spherical chamber of a few millimeters in radius and compressed by laser or heavy ion beams with powers in the order of 1014 W. The consequent plasma froming at the center of the chamber is an essential issue for fusion. The hydrodynamical instabilities during the fuel compression process arising in the conventional ICF technique leads to a decline in energy efficiency. The new plans for reducing instabilities involve compression of the fuel chamber in two stages using laser or ion beams. In the first stage, fuel is preheated by laser or ion and in the second phase, relativistic electrons are constructed by 1015 -W laser phases in the fuel. This heating method has come to be known as a fast “ignition method”. More recently, cylindrical rather than spherical fuel chambers with magnetic control in the plasma domain have been also considered. In this work, fast ignition method in cylindrical fuel chambers will be investigated and transportation of the relativistic electrons will be calculated using MCNP code and the Fokker–Planck program. Furthermore, the transfer rate of relativistic electron energy to the fuel will be calculated. Our calculations show that the fast ignition method and cylindrical chambers guarantee a higher energy efficiency than the one-step ignition and that it can be considered an appropriate substitute for the current ICF techniques.

Investigation of vertical vibrations of a railway turnout is important in designing track components under moving loads of trains. In this paper, the turnout is simulated by a linear finite element model with modal damping. A section of the turnout has a length of 36 sleeper spans surrounding the crossing. Rails and sleepers are modeled with uniform Rayleigh- Timoshenko beam elements. The rails are connected via rail pads (linear springs) to the sleepers, which rest on an elastic foundation. The rolling stocks are discrete systems of masses, springs, and dampers. By passing the trains at a constant speed, only vertical dynamics (including roll and pitch motions) is studied. The wheel-rail contact is modeled using a non-linear Hertzian spring. The train-track interaction problem is solved numerically by using an extended state space vector approach in conjunction with modal superposition for the turnout. The results show that the rail discontinuity at the frog leads to an increase in the wheel-rail contact force. Both smooth and irregular transitions of the wheels from the wing rail to the crossing nose have been examined for varying speeds of the vehicle. Under perfect conditions, the wheels will change quite smoothly from rolling on the wing rail to rolling on the nose. The impact at the crossing will then be small, giving a maximum wheel-rail contact force which is only 30-50 per cent larger than the static contact force. For uneven transitions, the severity of the impact loading at the crossing depends strongly on the train speed. The increase in the contact force, as compared with the static force, is in the order of 100 per cent at 70 km/h and 200 per cent at 150 km/h.

A rectangular rod is placed in a flow field flowing parallel to a flat plate. Effect of chord-thickness ratio of rectangular rod on developing vortex shedding downstream to the rod is studied. Then, for each one of the aspect ratios, the distance of the rod from the neighboring flat plate is reduced until the rod sticks to the flat plate. In each case, the effect of the flat plate boundary layer on Strouhal number and the contrary effect of the boundary layer on vortex shedding from the rectangular rod are studied. Results show that as the rectangular rod enters into the flat plate boundary layer, vortex generation from the closest side of the rod reduces, thereby reducing the Strouhal number as well. Finally, when the rectangular rod sticks to the flat plate, a stationary wake forms downstream the rod and sticks to the flat plate. Meanwhile, the boundary layer over the flat plate is disturbed effectively and heat transfer coefficient from the flat plate is enhanced by an average of 50% and up to 200% in some places, locally.

In this paper, the boundary-based estimation of pressure distribution in the cardiovascular system is investigated using two dimensional flow images. The conventional methods of non-invasive estimation of pressure distribution in the cardiovascular flow domain use the differential form of governing equations. This study evaluates the advantages of using the integral form of the equations in these calculations. The concepts provided with the Boundary Element Method (BEM) together with the boundary-based image segmentation tools are used to develop a fast calculation method. Boundary-based segmentation provides BEM with domain pixel extraction, boundary meshing, wall normal vector calculation, and accurate calculation of boundary element length. The integral form of the governing equations are reviewed in detail and the analytic value of integral constants at singular points are provided. The pressure data on boundary nodes are calculated to obtain the pressure data at every point in the domain. Therefore, the calculation of domain pressure could be considered as a post-processing procedure, which is an advantage of this approach. Both the differential and integral-based formulations are evaluated using mathematical Couette test flow image whose pressure domain is available. The resulting pressure distributions from both methods will be compared. According to the results obtained from this study, the use of BEM for estimating pressure values from a non-invasive flow image has the following advantages: reduced computational domain from two to one dimension, flexible calculation of pressure data at arbitrary points or at finer spatial resolutions, robustness against noise, less concern for its stability and compatibility, accuracy, and lower meshing attempts.

Prediction of SCC risk of austenitic stainless steels in aqueous chloride solution and estimation of the time to failure as a result of SCC form important and complicated topics for study. Despite the many studies reported in the literature, a formulation or a reliable method for the prediction of time to failure as a result of SCC is yet to be developed. This paper is an effort to investigate the capability of artificial neural network in estimatiing the time to failure for SCC of 304 stainless steel in aqueous chloride solution and to provide a sensitivity analysis thereof. The input parameters considered are temperature, chloride ion concentration, and applied stress. The time to failure is defined as the output parameter and the key criterion to evaluate the effective parameters. The statistical performance of the neural network is expressed as the average of three learning and testing results. The SCC database is divided into two sections designated as the learning set and the testing set. The output results show that artificial neural network can predict the time to failure for about 74% of the variance of SCC experimental data. Furthermore, the sensitivity analysis also exhibits the effects of input parameters on SCC of 304 stainless steel in aqueous chloride solutions.

A review of pavement thickness designs shows that two kinds of failure criteria are used in most cases. They are: 1) The tension strain under the asphalt layer that causes cracking; and 2) the vertical compression strain on the sub-grade that causes deflection. In this study, various factors affecting thickness design are first defined and more than 216 pavement conditions are introduced. Structures are analyzed using the Flex pass program and their strains and stresses are investigated severally by choosing the failure criteria one at a time.