Sirjan University of Technology

Sīrjān, Iran

Sirjan University of Technology

Sīrjān, Iran
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Shamsoddini R.,Sirjan University of Technology
International Journal of Computational Methods | Year: 2017

In the present study, for the first time, the flow and mass transfer in the rotary micropump-micromixers were investigated by the SPH method. In fact, the present work shows the ability of the SPH method to model the mixing process due to pumping action. The incompressible SPH method applied for modeling is improved by the kernel gradient corrective tensor, a particle shifting algorithm, and an improved periodic boundary condition. SPH is a proper method for modeling the mixing process because there is no modeling for the convective terms and so, the false diffusion is not observed in the SPH modeling. In the present study, first, a viscous micropump comprising a microchannel in which a circular cylinder rotates with special eccentricity is modeled and validated. Then, the geometry is manipulated in order to achieve a desirable micromixer. © 2018 World Scientific Publishing Company


Ehsaeyan E.,Sirjan University of Technology
Journal of Information Systems and Telecommunication | Year: 2017

In this paper, we propose an efficient noise robust edge detection technique based on odd Gaussian derivations in the wavelet transform domain. At first, new basis wavelet functions are introduced and the proposed algorithm is explained. The algorithm consists of two stage. The first idea comes from the response multiplication across the derivation and the second one is pruning algorithm which improves fake edges. Our method is applied to the binary and the natural grayscale image in the noise-free and the noisy condition with the different power density. The results are compared with the traditional wavelet edge detection method in the visual and the statistical data in the relevant tables. With the proper selection of the wavelet basis function, an admissible edge response to the significant inhibited noise without the smoothing technique is obtained, and some of the edge detection criteria are improved. The experimental visual and statistical results of studying images show that our method is feasibly strong and has good edge detection performances, in particular, in the high noise contaminated condition. Moreover, to have a better result and improve edge detection criteria, a pruning algorithm as a post processing stage is introduced and applied to the binary and grayscale images. The obtained results, verify that the proposed scheme can detect reasonable edge features and dilute the noise effect properly.


Ehsaeyan E.,Sirjan University of Technology
Journal of Telecommunication, Electronic and Computer Engineering | Year: 2017

Edge detection is an image processing technique for finding the boundaries of objects within images. It works by detecting discontinuities in brightness. In this paper, we develop the Canny edge detector, introduce wavelet basis functions of nth Gaussian derivative and utilize them to extract the edge. At first, the principle of the edge detection by the wavelet transform is given briefly and new basis of wavelet functions are introduced and admissibility conditions of them are discussed. Then, the theoretical edge detection analysis of three significant edge types (step, ramp and stage) via new wavelet basis functions is studied, and relevant formulas are derived. The theory of the step response in the x, y and arbitrary direction is given and the effect of smoothing filter is obtained. We show that all introduced wavelet functions can detect the breakpoint of the step function. A model of the ramp function is presented and an approximation of it is used to simplify the results. © 2017, Universiti Teknikal Malaysia Melaka. All rights reserved.


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.

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