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Sajjadi H.,Shahid Bahonar University of Kerman | Beigzadeh Abbassi M.,Sirjan University of Technology | Kefayati G.H.R.,Flinders University
Journal of Mechanical Science and Technology | Year: 2013

In this paper, lattice Boltzmann simulation of turbulent natural convection with large-eddy simulations (LES) in a square cavity which is filled by water/copper nanofluid has been investigated. The present results are validated by experimental data at Ra = 1.58×109. This study is conducted for high Rayleigh numbers (Ra = 107-109) and volume fractions of nanoparticles (0 ≤ Φ ≤ 0.06). In this research, the effects of nanoparticles are displayed on streamlines and isotherms counters, local and average Nusselt numbers. The average Nusselt number is enhanced by the augmentation of nanoparticle volume fraction in the base fluid while the manner has an erratic trend toward different Rayleigh numbers. © 2013 The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg.


Marzocca P.,Clarkson University | Fazelzadeh S.A.,Shiraz University | Hosseini M.,Sirjan University of Technology
Journal of Thermal Stresses | Year: 2011

Functionally Graded Materials (FGM) have attracted significant interest as heat-shielding materials for space vehicle, skin sub-structures, gas turbine blades technologies, and many other high-temperature industrial applications. This paper reviews the state-of-the-art in linear and nonlinear aero-thermo-elasticity of FGM panels with emphasis on the authors' contributions to the topic. An overview of the pertinent literature discussing the linear and nonlinear behavior of flat and curved panels when exposed to high temperature supersonic flow fields is presented first. The effect of material property dependency on temperature is also discussed. The study addresses divergence and flutter and methodologies used to determine these aerothermo- elastic instabilities. In particular, critical and post-critical behaviors for panels in presence of thermal loads are addressed, along with a series of divergence, flutter, and post-flutter results obtained with linear/nonlinear dynamics approaches. Regular and chaotic motions regime are determined through qualitative tools, such as bifurcation analysis using Poincaré maps, panel time history, phase-space evolutions, and frequency spectra, and with quantitative tools, such as the Lyapunov's exponents and dimensions. Finally, conclusions and directions for further work in the field are presented. Copyright © Taylor & Francis Group, LLC.


Ehsaeyan E.,Sirjan University of Technology
Iranian Journal of Electrical and Electronic Engineering | Year: 2016

Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising and destroys the flatness of homogenous area. Wavelets are not very effective in dealing with multidimensional signals containing distributed discontinuities such as edges. This paper develops an effective shearlet-based denoising method with a strong ability to localize distributed discontinuities to overcome this limitation. The approach introduced here presents two major contributions: (a) Shearlet Transform is designed to get more directional subbands which helps to capture the anisotropic information of the image (b) coefficients are divided into low frequency and high frequency subband. Then, the low frequency band is refined by Wiener filter and the high-pass bands are denoised via NeighShrink model. Our framework outperforms the wavelet transform denoising by %7.34 in terms of PSNR (peak signal-to-noise ratio) and %13.42 in terms of SSIM (Structural Similarity Index) for ‘Lena’ image. Our results in standard images show the good performance of this algorithm, and prove that the algorithm proposed is robust to noise. © 2016, Iran University of Science and Technology. All rights reserved.


Asadi M.,Sirjan University of Technology
Journal of Rock Mechanics and Geotechnical Engineering | Year: 2016

Development of accurate and reliable models for predicting the strength of rocks and rock masses is one of the most common interests of geologists, civil and mining engineers and many others. Due to uncertainties in evaluation of effective parameters and also complicated nature of geological materials, it is difficult to estimate the strength precisely using theoretical approaches. On the other hand, intelligent approaches have attracted much attention as novel and effective tools of solving complicated problems in engineering practice over the past decades. In this paper, a new method is proposed for mining descriptive Mamdani fuzzy inference systems to predict the strength of intact rocks and anisotropic rock masses containing well-defined through-going joint. The proposed method initially employs a genetic algorithm (GA) to pick important rules from a preliminary rule base produced by grid partitioning and, subsequently, selected rules are given weights using the GA. Moreover, an information criterion is used during the first phase to optimize the models in terms of accuracy and complexity. The proposed hybrid method can be considered as a robust optimization task which produces promising results compared with previous approaches. © 2016 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences.


Ehsaeyan E.,Sirjan University of Technology
Iranian Journal of Electrical and Electronic Engineering | Year: 2016

The use of wavelets in denoising, seems to be an advantage in representing well the details. However, the edges are not so well preserved. Total variation technique has advantages over simple denoising techniques such as linear smoothing or median filtering, which reduce noise, but at the same time smooth away edges to a greater or lesser degree. In this paper, an efficient denoising method based on Total Variation model (TV), and Dual-Tree Complex Wavelet Transform (DTCWT) is proposed to incorporate both properties. In our method, TV is employed to refine low-passed coefficients and DTCWT is used to shrink high-passed noisy coefficients to achieve more accurate image recovery. The efficiency of our approach is firstly analyzed by comparing the results with well-known methods such as probShrink, BLS-GSM, SUREbivariate, NL-Means and TV model. Secondly, it is compared to some denoising methods, which have been reported recently. Experimental results show that the proposed method outperforms the Steerable pyramid denoising by 8.5% in terms of PSNR and 17.5% in terms of SSIM for standard images. Obtained results convince us that the proposed scheme provides a better performance in noise blocking among reported state-of-the-art methods. © 2016, Iran University of Science and Technology. All rights reserved.


Jamalpoor A.,Iran University of Science and Technology | Hosseini M.,Sirjan University of Technology
Composites Part B: Engineering | Year: 2015

Background/purpose This paper deals with analysis of biaxial buckling behavior of double-orthotropic microplate system including in-plane magnetic field, using strain gradient theory. Methods Two Kirchhoff microplates are coupled by an internal elastic medium and also are limited to the external Pasternak elastic foundation. Utilizing the principle of total potential energy, the equilibrium equations of motion for three cases (out-of-phase buckling, in-phase buckling and buckling with a plate) are acquired. In this study, we assumed boundary conditions of all the edges are simply supported. In order to get exact solution for buckling load of system, Navier approach which satisfies the simply supported boundary conditions is applied. Results Variations of the buckling load of double-microplate system subjected to biaxial compression corresponding to various values of the thickness, length scale parameter, magnetic field, stiffness of internal and external elastic medium, aspect ratio, shear stiffness of the Pasternak foundation and biaxial compression ratio are investigated. Furthermore, influence of higher modes on buckling load is shown. By comparing the numerical results, it is found that dimensionless buckling load ratio for in-phase mode is more than those of out of phase and one microplate fixed. Also it is shown that the value of buckling load ratio reduces, when non-dimensional length scale parameter increases. Conclusion However, we found when properties of plate are orthotropic the buckling load ratio is more than isotropic state. Also, by considering the effect of magnetic field, non-dimensional buckling load ratio reduces. © 2015 Elsevier Ltd All rights reserved.


Mahmoodabadi M.J.,Sirjan University of Technology | Momennejad S.,Islamic Azad University | Bagheri A.,Guilan University
Information Sciences | Year: 2014

Regulation and tracking of system states to the desired points or trajectories are two common tasks in the field of control engineering. For optimum performance of a controller, the appropriate selection of its parameters is of utmost importance. Furthermore, when the initial conditions of the system change, the controller with the previous parameters would be not optimum in the new conditions. To overcome these obstacles, in this paper, an online optimal Decoupled Sliding Mode Control (DSMC) approach is introduced. Firstly, to determine the optimum parameters of DSMC, an improved Particle Swarm Optimization (PSO) algorithm is applied. Next, to adapt the optimal controller to any initial condition, the Moving Least Squares (MLS) approximation is utilized. Finally, the proposed online optimal DSMC is successfully applied to a ball and beam system. The comparative studies are provided to verify the effectiveness of the proposed control scheme. © 2014 Elsevier Inc. All rights reserved.


Mahmoodabadi M.J.,Sirjan University of Technology | Taherkhorsandi M.,Guilan University | Bagheri A.,Guilan University
Neurocomputing | Year: 2014

The aim of this paper is to present novel Multi-objective Particle Swarm Optimization (MOPSO) called Ingenious-MOPSO and compare its capability with three well-known multi-objective optimization algorithms, modified NSGAII, Sigma method, and MOGA. The application of this investigation is on an intellectual challenge in robotics, that is, a biped robot walking in the lateral plane on slope. Recently, a number of researches have been done on the walking of biped robots in the sagittal plane; however, biped robots require the ability to step purely in the lateral plane in facing obstruction, such as a wall. Hence, this paper introduces an optimal robust sliding tracking controller tuned by Ingenious-MOPSO to address the problem of heavy nonlinear dynamics and tracking systems of the biped robots which walk in the lateral plane on slope. Two phases of a biped robot, single support phase and double support phase; and also impact are regarded to control the robot. In the sliding mode controller, the heuristic parameters are usually determined by a tedious and repetitive trial-and-error process. By using Ingenious-MOPSO, the trial-and-error process is eliminated and the optimal parameters are chosen based on the design criteria. In the proposed algorithm, Ingenious-MOPSO, the rate of convergence and diversity of solutions are enhanced simultaneously, and innovative methods are proposed to select the global and personal best positions for each particle. Moreover, a new fuzzy elimination technique is suggested for shrinking the archive which promotes the diversity of solutions. A turbulence operator is utilized to evade local optima, for further improving the search ability. Numerical results and analysis demonstrate the superiority of Ingenious-MOPSO over three effectual multi-objective optimization algorithms. © 2013 Elsevier B.V.


Ehsaeyan E.,Sirjan University of Technology
International Journal of Engineering, Transactions B: Applications | Year: 2016

Wiener filter suppresses noise efficiently. However, it makes the out image blurred. Curvelet preserves the edges of natural images perfectly, but, it produces visual distortion artifacts and fuzzy edges to the restored image, especially in homogeneous regions of images. In this paper, an efficient image denoising framework based on Curvelet transform and wiener filter is proposed, which can reduce noise better than these methods. The performance of introduced scheme is evaluated in terms of two important denoising criteria, PSNR and SSIM on standard test images in different noise levels. Three famous thresholding 'soft', 'semisoft' and 'hard' are applied to noisy images and results are fused by the wavelet transform to form restore images. Our framework outperforms the curvelet transform denoising by %6.3 in terms of PSNR and %5.9 in terms of SSIM for 'Lena' image. The visual outputs show that false artifacts, parasite lines and the blurring degree of output images, are reduced significantly. The obtained results reveal the superiority of our framework over recent reported methods. © 2016, Materials and Energy Research Center. All rights reserved.


Ghanizadeh A.R.,Sirjan University of Technology
Advances in Civil Engineering | Year: 2016

Pavement construction is one of the most costly parts of transportation infrastructures. Incommensurate design and construction of pavements, in addition to the loss of the initial investment, would impose indirect costs to the road users and reduce road safety. This paper aims to propose an optimization model to determine the optimal configuration as well as the optimum thickness of different pavement layers based on the Iran Highway Asphalt Paving Code Number 234 (IHAP Code 234). After developing the optimization model, the optimum thickness of pavement layers for secondary rural roads, major rural roads, and freeways was determined based on the recommended prices in "Basic Price List for Road, Runway and Railway" of Iran in 2015 and several charts were developed to determine the optimum thickness of pavement layers including asphalt concrete, granular base, and granular subbase with respect to road classification, design traffic, and resilient modulus of subgrade. Design charts confirm that in the current situation (material prices in 2015), application of asphalt treated layer in pavement structure is not cost effective. Also it was shown that, with increasing the strength of subgrade soil, the subbase layer may be removed from the optimum structure of pavement. Copyright © 2016 Ali Reza Ghanizadeh.

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