فصلنامه مدل سازی در مهندسی
پیاپی 39 (زمستان 1393)

In recent years, damage detection and structural health monitoring methods for civil and mechanical structures, have been developed in different fields. Structural health monitoring is the implementation of a damage identification strategy to the civil engineering infrastructures. Damage is defined as changes to the material and/or geometric properties of these systems, including changes to the boundary conditions and system connectivity. Damage affects the current or future performance of such systems. Structural health monitoring and damage detection has several techniques, the methods are categorized based on the type of measured data used, and/or the technique used to identify the damage from the measured data. Wavelet transform is relatively new mathematical tool for signal processing. Wavelet transform gives more information on non-stationary signal that the Fourier transform was unable to provide them. One of the most important issue of application of the mathematical transforms such as wavelet, is structural health monitoring and structural damage detection. Especially the identification of damage in structures at the beginning is important. In this paper a simple method based on Wavelet transform has been utilized in order to localize and quantify the crack in simple supported beam; in which, the deflection of the beam subject to static loading would be decomposed by discrete wavelet transforms. In decomposition diagrams has been assessed for various scenarios of damage. Finally the performance of the applied method has been evaluated for different state of cracking.

This article introduces a method to detect and remove unipolar impulse noises from digital images. In this study, proposed method is a repetitive procedure which each repeat contain three steps. Also, proposed method can be based on two detection algorithms that are introduced to detect unipolar impulse noises. In this research, unipolar impulse noises with 3 different distribution types are modeled and added to original image to produce noised image. Then, image is reconstructed based on proposed method from produced noised image. Finally, reconstructed image is evaluated in comparison to original image. Detected noises by introduced algorithms are evaluated by Overall Accuracy index. Also, quality of the reconstructed image is evaluated by Peak Signal to Noise Ratio (PSNR) index. Evaluation results are shown that proposed method based on two detection algorithms is better than regular and adaptive two-pass median filters. Quality of the reconstructed images by proposed method is high than results of regular and adaptive two-pass median filters. The average enhancement in quality is equivalent with increasement 5.37 and 4.17 decibels in PSNR index respectively.

In this paper, improvement of the transient stability of power systems using the Flexible AC Transmission Systems (FACTS) parallel devices (ASVC and SVC) has been analyzed. Control methods that have been used in this paper, based on Lyapunov theory and Transient Energy Function (TEF) is used. Controls the damping system ensures However, in order to improve the damping rate of the intelligent optimization methods are used. In this direction, a new optimization method Shuffled Frog Leaping (SFL) was used. The objective function considered in this way, which tends to be the dominant attenuation due to practical constraints. Simulation results show the effectiveness of the proposed optimal control method.

This study presents the phenomena occuring in small scale single-pellet for the oxidative coupling of methane where heat transfer plays an important role. Computational fluid dynamics (CFD) is used as a tool for obtaining detailed rate and temperature profiles through the porous catalytic pellet where reaction and diffusion are competing. Inter particle temperature and concentration gradients were taken into account by solving heat transfer coupled with continuity equations in the catalyst pellet. In the heat transfer equation the source term of energy due to high exothermic of reaction is considered. Subsequent to achieving this goal, two external programs are successfully implemented to CFD-code as kinetic and heat of reaction terms. This simulation results show the reaction is favorite for the beginning of the pellet and for downstream of the pellet domain the diffusion is predominates. The results of CFD simulation indicate that temperature variation within the catalyst pellet is < 1K due to the completion of exothermic oxidation reactions. Also, the results show that exothermic oxidation reactions occur before endothermic coupling reaction in the pellet length.

Nowadays, the concern about strike of disruptions and its consequent huge losses has motivated many researchers to design reliable supply chain networks. As well, inherent uncertainty of input data is a momentous issue which should be considered carefully in the design of supply chain networks due to its adverse effect on quality of strategic, tactical and operational decisions. Therefore, this paper presents a novel model for designing a reliable closed-loop supply chain network in which a new reliability method is introduced. The propounded model not only minimizes the total cost, also efficiently finds a robust network under different kind of disruptions. To cope with imprecision of parameters, an effective possibilistic programming approach is employed. Finally, a real industrial case is used to demonstrate the effectiveness and applicability of the developed fuzzy optimization model.

In this paper, a new load pattern is proposed for pushover analysis of base isolated structures. Accuracy of the proposed load pattern and other conventional load patterns is evaluated through two sample structures under two ensembles of earthquake records (Near fault and Far fault records). Seven earthquake records are considered in each group. The resulted responses from each pushover analysis are compared with the responses resulted from the nonlinear time history analysis. The results show that the accuracy of the proposed load pattern in estimating the nonlinear response of the sample structures is more than the other load pattern.

The key of Reactive Power Planning (RPP), or Var planning and reactive power dispatch, are the optimal allocation of reactive power sources considering location and size. Traditionally, the locations for placing new Var sources were either simply estimated or directly assumed. Recent research works have presented some rigorous optimization based methods in RPP. The reactive power dispatch and planning is a large-scale non-convex, nonlinear programming (NLP) problem with real and discrete variables that presents a high degree of complexity for application in real electric power systems (EPS). This paper addresses an improved gravitational search algorithm (GSA) with strength Pareto front to find the feasible optimal solution of the RPP problem with various generator constraints in power systems. For practical generator operation, many nonlinear constraints of the generator, such as ramp rate limits, generation limits, transmission line loss and non-smooth cost functions are all considered using the proposed method. Effectiveness of the proposed method is demonstrated for two different systems, including 6 and 54 unit generating in comparison with the performance of the other recently optimization algorithms reported in the literature in terms of the solution quality and computation efficiency. The results analysis confirms that the proposed approach has an excellent capability to determine optimal solution of the RPP problems over the other existing methods and enhances efficiently the solutions quality of the power systems.

The growing use of industrial machinery, household appliances and etc, has increased undesirable noises. Thus, the need to control and reduce the undesirable noises in a closed space has caused a lot of interest in recent years. In this paper, the behavior of sound waves in a closed space is investigated using finite difference time domain method. For this reason, firstly, the wave equation is derived using the mass and momentum conservation equation and adiabatic state equation for an ideal compressible fluid. Then, the boundary condition equation for a closed space is obtained using the momentum conservation law and wall impedance equation. The obtained equations are discritized based on the finite difference time domain method. Finally, the wave equation is solved under the wall boundary condition with arbitrary absorption coefficient and impulse source initial condition. The results show the capability of the method for solving this kind of problems.

Fleet selection in open-pit mines is of vital importance. Inappropriate selection of fleet can be influential on the project economics in two ways; failure in achieving production objectives and increase the attributed costs due to increase in the shipment time. Usually fleet design is fulfilled in the forms of either allocating or dispatching aiming to production maximization and cost minimization. Simulation technique, one of the available fleet selection methods, allows designers to study a system in a virtual environment without executing it in the real world, to technically and economically evaluate its efficiency. In this paper, at first using the simulation technique, transportation system of the Songun copper mine was simulated in the Arena software and then by defining new systems, efficiency of the available fleet was improved. On the basis of the obtained results it was observed that a fleet of 100 t dump trucks, 6.1 m3 front end loaders, 7.0 m3 shovel and 4.6 m3 excavator with weekly production of 550,000 tones and 0.83$ per/ m3 is the best possible alternative.

Laminar flow of a non-Newtonian fluid over a moving flat solid boundary has been investigated. The power-law model was used for describing the non-Newtonian behavior of the fluid. The fluid was stationary at free stream and the motion of the solid boundary imposed the fluid to flow. Velocity of the solid boundary varied linearly along its length which is called stretching sheet. Also, the velocity of this boundary increased in time as a hyperbolic function. A new similarity variable for this type of transient motion of the stretching sheet based on the non-Newtonian behavior of the fluid has been proposed. This similarity variable transforms three independent variable (t,x,y) into an independent variable (η). By the use of this transformation, the governing partial differential equations of mass and momentum conservations were transformed into a single non-linear ordinary differential equation. Also, a numerical algorithm based on the finite difference method was proposed to solve the obtained non-linear differential equation. The proposed similarity variable reduced the complexity of the flow simulation and it represented all the three independent variables of the physical phenomenon at the same time. To see the results of the similarity transformation and the numeric algorithm, effects of the fluid and flow characteristics on the hydrodynamic behavior of the flow have been investigated.

This study deals with artificial neural network (ANN) modeling of a biodiesel production using waste cooking oil to predict the biodiesel purity. developed ANN was a feed forward back propagation network with one input, one hidden and one output layers. The input parameters for the ANN were methanol/oil molar ratio (3:1–9:1), temperature (45–65‬‬‬‬‬‬‬‬‬‫‪‭ °C), and mixing intensity (200–600 rpm) and the output parameter was biodiesel purity. The biodiesel with best purity was produced at methanol/oil molar ratio, of 6:1; mixing intensity, of 600 rpm and reaction temperature of 65 °C. Different transfer functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the ANN model can predict the biodiesel yield quite well with correlation coefficient (R) 0.99966. We can conclude that ANNs can be used to predict the biodiesel yield from used waste cooking oil.