International Journal of Engineering
Volume:27 Issue: 9, Sep 2014

Gas hydrates attracted worldwide attention due to their potential as huge energy resource in the recent decades. Effective parameters which influence the formation of hydrates are high pressure, low temperature and water presence. HYSYS software is one of the major simulators which is widely used in chemical and thermodynamic processes.This research was conducted to simulategas hydrate formation of Lavan-3 gas well and Salman gas field using the HYSYS software. The steady state simulation of hydrate formationwas performed by the Peng-Robinson equation of state. The predicted data were compared with experimental ones. It was concluded that HYSYS is able to predict hydrate formation with the average absolute error of less than 1%. Two novel correlations were also developed to estimate hydrate formation conditions for natural gas.

There are different methods for the hydraulic analysis of water supply networks. In the solution process of most of these methods, a large system of linear equationsis solved in each iteration. This usually requires a high computational effort. Hardy Cross method is one of the approaches that do not need such aprocess and may converge to the solution through scalar divisions. However,this method has two short comings: first, initial discharges should satisfy continuity equation at each node; second a large number of iterations are required to converge to solution. In this article an algorithm is suggested for the selection of initial discharges that are close to the final results while the continuity equations are automatically established. This algorithm may be directly implemented in the Hardy Cross method. To reduce the number of iterations the Hardy Cross method is combined with third-order and sixteenthorder methods. The results of some numerical examples demonstrate that the use of the combined approach with the suggested initial guess reduces the number of iterations and hydraulic analysis time and the solutions converge with a high accuracy.

This paper proposes a new hybrid method based on Homomorphic filtering and anisotropic diffusion equations for image denoising. In this method, the Homomorphic filtering extracts the reflection and illumination components of a noisy image. Then a suitable image denoising method based on anisotropic diffusion is applied to each components with its special user-defined parameter. This hybrid scheme donates a flexibility and customizability to the method, due to its ability in properly enhancing images components. In order to evaluate the proposed method effectiveness, a number of experiments have been performed and the results have been compared with the results of other pioneering methods. The good results indicate superiority of the proposed method.

Over two decades, the problem of location dependent has been focused for improving the communication bandwidth-power efficiency of homogeneous networks. The efficiencies of communication links are weakened by the hidden terminal problem. Thus we propose a Fine–Tune strategy for analyzing the on-off communication region. We observed that the proposed technique was able to track and monitor the off-region nodes for improving the fidelity of the link. Testing of TCP variants was done to cross validate the value of on-demand bandwidth-power transmission parameters. The proposed technique of on–meet threshold (O-MT) was deployed in the network simulator tool of NS2 (v2.34) and while probing, the parameters of packet reception rate, packet dropping rate and throughput rate, bandwidth and power utilization rates were analyzed and found as best for TCP-EPRT (enhanced packet reception time) compared of TCP New Reno.

Multiple coupled circuit modeling (MCCM) of squirrel-cage induction motors (SCIMs), or winding function approach is the most detailed and complete analytical model used to analyze the performance of faulty SCIMs. Already, in various papers this approach has been used for 3-phases SCIMs, but this paper extends the above-mentioned model to 6-phases SCIMs. Various simulations of variative faults were carried out on faulty 6-phases SCIMs, and then, results obtained fromthe simulation were presented. The innovation of this paper is the first time simulation of broken bars and stator winding faults on 6-phases SCIMs using winding function approach with considering magnetic saturation effect that precise results were obtained as presented.

In this paper, an estimator for speech enhancement based on Laplacian Mixture Model (LMM)has been proposed. The proposed method, estimates the complex Discerete Fourier Transfor (DFT) coefficients of clean speech from noisy speech using the Minimum Mean Square Error(MMSE) estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of noise are assumed zero-mean Gaussian distribution. Furthermore, the MMSE estimator under speech presence uncertainty and the Laplacian mixture model were derived. It is shown that the proposed estimator has better performance than three estimators based on single Gaussian and single Laplacian models. Also under speech presence uncertainty the results become better.

This paper proposes a design for a mesoscale capsule robot which can be used in gaining diagnostic data and delivering medical treatment in inaccessible parts of the human body. After modeling the capsule robot system and determining its transfer function, an approach is presented for the capsule robot to control it: A PID-controlled closed-loop approach. A modified chaotic genetic algorithm is proposed in order to optimize the coefficients of the PID controller. Then, simulations are conducted to demonstrate the results for the proposed approach. Finally, the results are compared with those of similar works in the literature.

Nowadays many well-known firms may produce similar products at different prices in order to remain in the competitive environment. The price differences may cause substitution condition which motivates the customers to substitute similar cheaper product with an expensive one leading to an environment which is known as “customer-based price driven substitution”. This research proposes a new mathematical model towards a joint dynamic pricing and inventory control for seasonal and substitutable goods in a competitive market over a finite time planning horizon. It is assumed that the two substitute goods belong to two different rival firms. The objective is to determine the optimal price, order quantity and the number of periods for one product in the presence of symmetrical and asymmetrical substitutions such that the total profit of the related firm is maximized. First it is showed that total profit is a concave function of price which leads us to a unique optimal solution. To provide the optimal solution a simple algorithm is developed. Finally, in order to evaluate the performance of proposed algorithm a numerical example is presented.

This paper proposes an effective multi-objective differential evolution algorithm (MDES) to solve a permutation flow shop scheduling problem (PFSSP) with the modified Dejong''s learning effect. The proposed algorithm combines the basic differential evolution (DE) with local search and borrows the selection operator from NSGA-II to improve the general performance. First the problem is encoded with an appropriate rule to make the continuous nature of DE suitable for flow shop problems. Second, insert based local search is added in the initialization stage, as well as in each iteration to speed up convergence. The former guarantees that the algorithm commences with better solutions while the latter focuses the algorithm on promising areas. Third, in each generation, in order to improve diversity, two populations are introduced, current pop and advanced pop. The best solutions of each iteration are stored in the current pop, while the less than desirable solutions are added to the advanced pop. At the end of each generation, the two are combined and better individuals are selected for the next generation. The algorithm is then tested on benchmark problems to demonstrate its effectiveness and the results are discussed. Finally, a truncated version of Dejong''s learning effect is proposed and MDES is used to solve the permutation flow shop with the modified learning effect.

As customers are the main asset of any organization, customer churn management is becoming a major task for organizations to retain their valuable customers. In earlier studies, the applicability and efficiency of hierarchical data mining techniques for churn prediction by combining two or more techniques have been proved to provide better performances than many single techniques over a number of different domain problems. This paper considers a hierarchical model by combining three data mining techniques containing two different fuzzy prediction networks and a regression technique for churn prediction, namely Alpha-cut Fuzzy C-Means (αFCM), Improved Fuzzy ARTMAP and Cox proportional hazards regression model, respectively. In particular, the first component of the hierarchical model aims to cluster data in two churner and non-churner groups applying the alpha-cut algorithm and filter out unrepresentative data or outliers. Then, the clustered and representative data as the outputs are used to assign customers to churner and non-churner groups by the second technique. Finally, the correctly classified data are used to create the Cox proportional hazards model. To evaluate the performance of the proposed hierarchical model, the Iranian mobile dataset is considered. The experimental results show that the proposed model outperforms the single Cox regression baseline model in terms of prediction accuracy, Type I and II errors, RMSE, and MAD metrics.

The mesoporous carbon (CMK-3) functionalized with ethylenediamine (EDA) has been propered (CMK- 3-EDA) and used as a new mesoporous adsorbent for removal of Cu(II) and Pb(II) cations from aqueous solutions. Nitrogen adsorption–desorption measurements (BET) show that surface area, pore size and pore volume of CMK-3 have significantly changed after amine modification. The BET surface area and pore diameter of functionalized product were 344.74 m2. g−1 and 28.61Å, respectively. The adsorption conditions including contact time, pH value and adsorbent dosage of the sample solution have been studied in batch system and then determined by means of flam atomic absorption spectrometry. The adsorption capacity was 188.2 mg. g−1 and 196.64 mg. g−1 for Cu(II) and Pb(II) ions, respectively. The obtained high adsorption capacity of CMK-3 functionalized with EDA is due to the amine functional groups formed on the surface of CMK-3 which can react with Pb(II) and Cu(II) ions. Results show that the new synthesized porous material is a highly effective for sorption of Pb(II) and Cu(II) ions in comparison to other adsorbents.

In this paper, the Taguchi method has been applied to optimize the heat treatment parameters for the corrosion resistance of 6061 aluminum alloy. The experimental design consisted of four parameters (aging temperature, aging time, quenching environment and NaCl concentration), each at three levels. Tafel polarization measurements were carried out to determine the corrosion resistance of the heat treatment samples. According to the mean of signal-to-noise ratio analysis, the corrosion resistance of AA6061-T6 was influenced significantly by the levels in the Taguchi orthogonalarray. The optimized parameters for corrosion resistance are 2 h for aging time, 200 °C for aging temperature, ice water for quenching media and environment with 0.5% for NaCl concentration. The percentage of contribution for each parameter was determined by the analysis of variance. The results showed that the NaCl concentration is the most significant parameter affecting the corrosion resistance of the AA6061.

The main aim of this work is devoted to numerical optimization of fin-pin arrangement in the double pipe heat exchanger. For this reason, heat exchanger which is used by Sahiti et al. was studied as an initial geometry. Since they did not consider the fin-pin arrangement effects, modification of their model by changing the fin arranges and using the Brent’s optimization algorithm based on the thermodynamically design concept, would be useful. In this work, by minimizing the entropy generation in constant heat duty per length and constant fins diameters D and changing the pin’s longitudinal (SL) and transversal (ST) distances, better results have been achieved. Results showed that, in all conditions entropy generation number decreased and consequently leads to reduction in pumping power and manufacturing costs.

In this paper, the problems of state estimation, tracking control and shape control in a micro-cantilever beam with nonlinear electrostatic actuation are investigated. The system’s partial differential equation of motion is converted into a set of ordinary differential equations by projection method. Observabillity of the system is proven and a state estimation system is designed using extended Kalman filter (EKF) algorithm. A tracking control system is designed to make a specific point of the beam follow a reference signal. The effect of mode selection to include in model on controller performance is also investigated. Based on the tracking controller a shape control algorithm is designed to form the shape of beam into a desired shape. The proposed algorithms are validated by numerical simulation and resulted in a promising performance.

Among different goals defined in vehicle design process, fuel consumption (FC) is one of the most important objectives, which significantly has taken into account lately, both by the customers and vehicle manufacturers. One of the significant parameters which impacts the vehicle FC is the efficiency of vehicle''s power train. In this paper, a half-toroidal continuously variable transmission (CVT) is considered as the vehicle power train. Its efficiency is sensitive to its geometry, and variation of its geometry can result the vehicle FC reduction. On the other hand, geometry variation affects its weight and fatigue life, which are considered as major contributing factors in the power train design. This paper aims to optimize half-toroidal CVT in order to minimize its weight, FC of the vehicle equipped with it, and provide the desired fatigue life. After introducing half-toroidal CVT, the method of calculating the mentioned objective functions is presented. A specific importance weight for each objective is considered. These weights are functions of their related objectives. A single objective optimization is implemented for each objective, and their optimal values are obtained. Then, these objectives are optimized simultaneously using Global Criterion method.

The present paper is devoted to implementation of the immersed boundary technique into the Fourier pseudo-spectral solution of the vorticity-velocity formulation of the two-dimensional incompressible Navier-Stokes equations. The immersed boundary conditions are implemented via direct modification of the convection and diffusion terms, and therefore, in contrast to some other similar methods, there is not an explicit external forcing function in the present formulation. At the beginning of each time step, the solenoidal velocities (also satisfying the desired immersed boundary conditions), are obtained and fed into a conventional pseudo-spectral solver, together with a modified vorticity. The classical explicit fourth-order Runge-Kutta method is used in time integration, and the boundary conditions are set at the beginning of each sub-step, in order to increase the time accuracy. The method is employed in simulation of some different test cases, including the flow behind impulsively started circular cylinder, oscillating circular cylinder in fluid at rest and insect-like flapping wing motion. The results show accuracy and efficiency of the method.

In this paper, a three-dimensional finite element (FE) model of carbon nanocones (CNCs) is proposed and used for obtaining Young''s modulus of CNCs. In this model, stretching and bending forces between carbon atoms are simulated using truss elements in ANSYS software. Then, the model is subjected to the tension and by obtaining the stiffness of the CNC and using elasticity theory, Young’s modulus is calculated. The results showed that for a fixed length of CNC, the modulus increase with the increase in diameter whereas it decreases by an increase in the apex angle. Also, Young’s modulus of double walled carbon nanocones (DWCNCs) obtained between the values of each layer. Furthermore, it is showed that elastic modulus can be effected by defects and their positions in CNC.

Haulage costs accounts for 45 to 60% of the total operating costs in large open pit mines. Cost efficiency and high reliability of semi mobile or combined «In Pit Crushing-Conveying (IPCC) and truck» systems compared to conventional truck-shovel systems alone, makes it more appealing to be utilized in modern mining activities. Semi mobile systems have the advantages of both systems, and its operating costs depend on the location of the in pit crushing unit. In this paper, the effective factors on determination of a suitable location of an IPCC are studied and it is investigated as a single hub location problem. The main concerns of the optimum location are minimizing haulage costs and choosing a location regarding the environmental concerns. The method is applied in Sarcheshmeh Copper Mine (SCM), and according to the results, locations C1 to C4 are candidate locations, and applying the hub model, location C2 on level 2450 is suggested to locate the IPCC.