Showing papers by "Amirkabir University of Technology published in 2012"
TL;DR: This survey tries to review all aspects of the covering problems by stressing the works after Schilling, Jayaraman, and Barkhi (1993).
540 citations
TL;DR: A new topology for cascaded multilevel converter based on submultileVEL converter units and full-bridge converters is proposed, optimized for various objectives, such as the minimization of the number of switches, gate driver circuits and capacitors, and blocking voltage on switches.
Abstract: In this paper, a new topology for cascaded multilevel converter based on submultilevel converter units and full-bridge converters is proposed. The proposed topology significantly reduces the number of dc voltage sources, switches, IGBTs, and power diodes as the number of output voltage levels increases. Also, an algorithm to determine dc voltage sources magnitudes is proposed. To synthesize maximum levels at the output voltage, the proposed topology is optimized for various objectives, such as the minimization of the number of switches, gate driver circuits and capacitors, and blocking voltage on switches. The analytical analyses of the power losses of the proposed converter are also presented. The operation and performance of the proposed multilevel converter have been evaluated with the experimental results of a single-phase 125-level prototype converter.
471 citations
TL;DR: A review of the literature about the durability of alkali-activated binders is presented in this article, focusing on resistance to acid attack, alkali−silica reaction, corrosion of steel reinforcement, resistance to high temperatures and to fire, and resistance to freeze-thaw.
388 citations
TL;DR: Numerical simulations are exploited to demonstrate the effectiveness of the pinning impulsive strategy proposed, which guarantees that the whole state-coupled dynamical network can be forced to some desired trajectory by placing impulsive controllers on a small fraction of nodes.
Abstract: In this paper, a new control strategy is proposed for the synchronization of stochastic dynamical networks with nonlinear coupling. Pinning state feedback controllers have been proved to be effective for synchronization control of state-coupled dynamical networks. We will show that pinning impulsive controllers are also effective for synchronization control of the above mentioned dynamical networks. Some generic mean square stability criteria are derived in terms of algebraic conditions, which guarantee that the whole state-coupled dynamical network can be forced to some desired trajectory by placing impulsive controllers on a small fraction of nodes. An effective method is given to select the nodes which should be controlled at each impulsive constants. The proportion of the controlled nodes guaranteeing the stability is explicitly obtained, and the synchronization region is also derived and clearly plotted. Numerical simulations are exploited to demonstrate the effectiveness of the pinning impulsive strategy proposed in this paper.
376 citations
TL;DR: This paper presents the Bee optimization method for harmonic elimination in a cascaded multilevel inverter, based on the food foraging behavior of a swarm of a honeybees, which has higher precision and probability of convergence than the genetic algorithm (GA).
Abstract: This paper presents the Bee optimization method for harmonic elimination in a cascaded multilevel inverter. The main objective in selective harmonic elimination pulsewidth modulation strategy is eliminating low-order harmonics by solving nonlinear equations, while the fundamental component is satisfied. In this paper, the Bee algorithm (BA) is applied to a 7-level inverter for solving the equations. The algorithm is based on the food foraging behavior of a swarm of a honeybees and it performs a neighborhood search combined with a random search. This method has higher precision and probability of convergence than the genetic algorithm (GA). MATLAB software is used for optimization and comparison of GA and BA. Simulation results show superiority of BA over GA in attaining accurate global minima and higher convergence rate. Also, its performance in 10 times run is the same as in 1 time run. Finally, for verifying purposes, an experimental study is performed.
337 citations
TL;DR: In this paper, the authors review relevant literature which deals with experimental evidence of material related and event related impact resistance parameters as well as the articles related to theoretical and numerical simulation of impact loading of fiber metal laminates.
292 citations
TL;DR: Electrospun polyvinyl alcohol (PVA)/chitosan nano-fibrous scaffolds have been synthesized with large pore sizes as potential matrices for nervous tissue engineering and repair and it could be concluded that addition of chitOSan to the PVA scaffolds enhances viability and proliferation of nerve cells, which increases the biocompatibility of the scaffolds.
Abstract: Among several attempts to integrate tissue engineering concepts into strategies to repair different parts of the human body, neuronal repair stands as a challenging area due to the complexity of the structure and function of the nervous system and the low efficiency of conventional repair approaches. Herein, electrospun polyvinyl alcohol (PVA)/chitosan nanofibrous scaffolds have been synthesized with large pore sizes as potential matrices for nervous tissue engineering and repair. PVA fibers were modified through blending with chitosan and porosity of scaffolds was measured at various levels of their depth through an image analysis method. In addition, the structural, physicochemical, biodegradability, and swelling of the chitosan nanofibrous scaffolds were evaluated. The chitosan-containing scaffolds were used for in vitro cell culture in contact with PC12 nerve cells, and they were found to exhibit the most balanced properties to meet the basic required specifications for nerve cells. It could be concluded that addition of chitosan to the PVA scaffolds enhances viability and proliferation of nerve cells, which increases the biocompatibility of the scaffolds. In fact, addition of a small percentage of chitosan to the PVA scaffolds proved to be a promising approach for synthesis of a neural-friendly polymeric blend.
282 citations
TL;DR: In this paper, the performance of concrete mixtures containing local metakaolin was investigated in terms of compressive strength, water penetration, sorptivity, salt ponding, Rapid Chloride Permeability Test (RCPT) and electrical resistivity at 7, 28, 90 and 180 days.
268 citations
TL;DR: In this article, an aqueous liquid crystalline dispersion of graphene oxide (GO) is in situ reduced in PU, resulting in a fine dispersion and a high degree of orientation of graphene sheets.
Abstract: Polyurethane (PU)-based composite films containing highly aligned graphene sheets are produced through an environmentally benign process. An aqueous liquid crystalline dispersion of graphene oxide (GO) is in situ reduced in PU, resulting in a fine dispersion and a high degree of orientation of graphene sheets. The PU particles are adsorbed onto the surface of the reduced graphene oxide (rGO), and the rGO sheets with a large aspect ratio of over 10 000 tend to self-align during the film formation when the graphene content is high enough, say more than 2 wt%. The resulting composites show excellent electrical conductivity with an extremely low percolation threshold of 0.078 vol%, which is considered one of the lowest values ever reported for polymer composites containing graphene. The electrical conductivity of the composites with high graphene contents presents significant anisotropy due to the preferential formation of conductive networks along the in-plane direction, another proof of the existence of the self-aligned, layered structure.
265 citations
TL;DR: A new function for the similarity of the generated pattern and the training image, based on a cross-correlation (CC) function, is proposed that can be used with both categorical and continuous training images, and the performance of CCSIM is tested.
Abstract: An important issue in reservoir modeling is accurate generation of complex structures. The problem is difficult because the connectivity of the flow paths must be preserved. Multiple-point geostatistics is one of the most effective methods that can model the spatial patterns of geological structures, which is based on an informative geological training image that contains the variability, connectivity, and structural properties of a reservoir. Several pixel- and pattern-based methods have been developed in the past. In particular, pattern-based algorithms have become popular due to their ability for honoring the connectivity and geological features of a reservoir. But a shortcoming of such methods is that they require a massive data base, which make them highly memory- and CPU-intensive. In this paper, we propose a novel methodology for which there is no need to construct pattern data base and small data event. A new function for the similarity of the generated pattern and the training image, based on a cross-correlation (CC) function, is proposed that can be used with both categorical and continuous training images. We combine the CC function with an overlap strategy and a new approach, adaptive recursive template splitting along a raster path, in order to develop an algorithm, which we call cross-correlation simulation (CCSIM), for generation of the realizations of a reservoir with accurate conditioning and continuity. The performance of CCSIM is tested for a variety of training images. The results, when compared with those of the previous methods, indicate significant improvement in the CPU and memory requirements.
249 citations
TL;DR: In this article, the laminar convective heat transfer of an alumina-water nanofluid flow inside a wide rectangular microchannel heat sink (94.3mm, 28.1mm and 580μm; length, width and height, respectively) both numerically and experimentally was studied.
TL;DR: In this article, the application of natural zeolite as a supplementary cementitious material has been investigated, and some mechanical and durability properties of concrete made with 15% and 30% of NZ are studied in comparison with concrete without NZ replacement.
TL;DR: It is shown that a broad class of stochastic optimization problems that are computationally intractable with the CVaR is efficiently solvable with the EVaR, and it is proved that if two distributions have the same EVsaR at all confidence levels, then they are identical at all points.
Abstract: This paper introduces the concept of entropic value-at-risk (EVaR), a new coherent risk measure that corresponds to the tightest possible upper bound obtained from the Chernoff inequality for the value-at-risk (VaR) as well as the conditional value-at-risk (CVaR). We show that a broad class of stochastic optimization problems that are computationally intractable with the CVaR is efficiently solvable when the EVaR is incorporated. We also prove that if two distributions have the same EVaR at all confidence levels, then they are identical at all points. The dual representation of the EVaR is closely related to the Kullback-Leibler divergence, also known as the relative entropy. Inspired by this dual representation, we define a large class of coherent risk measures, called g-entropic risk measures. The new class includes both the CVaR and the EVaR.
TL;DR: An investigation of the frontal brain of MDD patients using the wavelet-chaos methodology and Katz's and Higuchi's fractal dimensions (KFD and HFD) as measures of nonlinearity and complexity concludes that HFD is more discriminative than HFD of the gamma band for discriminating MDD and non-MDD participants.
TL;DR: The results show that CANFIS–GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems.
TL;DR: In this article, a generalized Moving Least Squares (MLS) algorithm is proposed to directly estimate derivatives of a function from the data, without any detour via derivatives of derivatives of the function.
Abstract: The Moving Least Squares (MLS) method provides an approxima- tion ^ u of a function u based solely on values u(xj) of u on scattered \meshless" nodes xj. Derivatives of u are usually approximated by derivatives of ^ u. In contrast to this, we directly estimate derivatives of u from the data, without any detour via derivatives of ^. This is a generalized Moving Least Squares technique, and we prove that it produces diuse derivatives as introduced by Nyroles et. al. in 1992. Consequently, these turn out to be ecient direct estimates of the true derivatives, without anything \diuse" about them, and we prove optimal rates of convergence towards the true derivatives. Numerical examples conrm this, and we nally show how the use of shifted and scaled polynomials as basis functions in the generalized and standard MLS approxi- mation stabilizes the algorithm.
TL;DR: In this article, a modified couple stress theory is developed for third-order shear deformation functionally graded (FG) micro beam, and the results obtained by the present model deviates significantly from those in which Poisson's effect is neglected.
TL;DR: The aim of this study is to investigate the large-scale algae production using Nannochloropsis sp.
Abstract: The aim of this study is to investigate the large-scale algae production using Nannochloropsis sp. in indoor open ponds. One of the key factors in open pond productivity is the uniformity of distribution of nutrients and CO2. Therefore, the effects of paddlewheel speeds (1.4, 2.1 and 2.8 rad s � 1 ) on the productivity were also evaluated. The culture system
TL;DR: In this article, the numerical solution of classes of fractional convection-diffusion equations with variable coefficients is solved by reducing the problem to the solution of linear algebraic equations by expanding the required approximate solution as the elements of shifted Legendre polynomials in time and the Sinc functions in space with unknown coefficients.
TL;DR: In this article, the authors proposed that by proper functionalization and mixing strategy of graphene its dispersion, and bonding to the polymeric matrix can be improved, and they then applied this strategy to graphene-epoxy system by amino functionalization of graphene oxide (GO).
Abstract: Dispersion of nanomaterials in polymeric matrices plays an important role in determining the final properties of the composites. Dispersion in nano scale, and especially in single layers, provides best opportunity for bonding. In this study, we propose that by proper functionalization and mixing strategy of graphene its dispersion, and bonding to the polymeric matrix can be improved. We then apply this strategy to graphene-epoxy system by amino functionalization of graphene oxide (GO). The process included two phase extraction, and resulted in better dispersion and higher loading of graphene in epoxy matrix. Rheological evaluation of different graphene-epoxy dispersions showed a rheological percolation threshold of 0.2 vol% which is an indication of highly dispersed nanosheets. Observation of the samples by optical microscopy, scanning electron microscopy (SEM), and atomic force microscopy (AFM), showed dispersion homogeneity of the sheets at micro and nano scales. Study of graphene-epoxy composites showed good bonding between graphene and epoxy. Mechanical properties of the samples were consistent with theoretical predictions for ideal composites indicating molecular level dispersion and good bonding between nanosheets and epoxy matrix.
TL;DR: Using the genetic algorithm, a total harmonic distortion minimization process is directly applied to the line-to-line voltage of the inverter, indicating superiority of this approach over the commonly used phase-voltage THD minimization approach.
Abstract: In this paper, total harmonic distortion (THD) minimization of the output voltage of multilevel inverters is discussed. An efficient approach in reducing the harmonic contents of the inverter's output voltage is THD minimization. In multilevel inverters with a fundamental frequency switching strategy (each switch turning on and off once per output cycle), the switching angles can be selected so that the output THD is minimized (such as the so-called optimal-minimization-of-THD strategy). To obtain the optimum switching angles, an optimization algorithm is applied to the output-voltage THD. In three-phase multilevel inverters, the optimization algorithm is commonly applied to the phase voltage of the inverter. This results in the minimum THD in phase voltage but not necessarily in the line-to-line minimum THD, whereas in three-phase applications, the line-voltage harmonics are of the main concern from the load point of view. In this paper, using the genetic algorithm, a THD minimization process is directly applied to the line-to-line voltage of the inverter. This paper is based on a seven-level inverter. To verify the simulation results, a seven-level-cascaded-H-bridge-inverter-based hardware prototype, including an ATMEGA32 AVR microcontroller, has been implemented. Both simulation and experimental results indicate superiority of this approach over the commonly used phase-voltage THD minimization approach.
TL;DR: It is shown that the proposed improved PSVG is less sensitive to noise and therefore more robust compared with PSVG, and used in the wavelet-chaos neural network model of Adeli and c-workers in place of the Katz fractality dimension results in a more accurate diagnosis of autism, a complicated neurological and psychiatric disorder.
Abstract: Recently, the visibility graph (VG) algorithm was proposed for mapping a time series to a graph to study complexity and fractality of the time series through investigation of the complexity of its graph. The visibility graph algorithm converts a fractal time series to a scale-free graph. VG has been used for the investigation of fractality in the dynamic behavior of both artificial and natural complex systems. However, robustness and performance of the power of scale-freeness of VG (PSVG) as an effective method for measuring fractality has not been investigated. Since noise is unavoidable in real life time series, the robustness of a fractality measure is of paramount importance. To improve the accuracy and robustness of PSVG to noise for measurement of fractality of time series in biological time-series, an improved PSVG is presented in this paper. The proposed method is evaluated using two examples: a synthetic benchmark time series and a complicated real life Electroencephalograms (EEG)-based diagnostic problem, that is distinguishing autistic children from non-autistic children. It is shown that the proposed improved PSVG is less sensitive to noise and therefore more robust compared with PSVG. Further, it is shown that using improved PSVG in the wavelet-chaos neural network model of Adeli and c-workers in place of the Katz fractality dimension results in a more accurate diagnosis of autism, a complicated neurological and psychiatric disorder.
TL;DR: In this article, a green method for the synthesis of silver nanoparticles on the cotton fabric surface through using Tollens' reagent was introduced, where silver nitrate (AgNO3) was transformed to Ag2O followed by an aqueous solution with ammonia.
TL;DR: In this article, the effect of electrospinning duration on some physical andmechanical properties of polyurethane (PU) electrospunwebs is investigated for potential applications such as pro-tective clothing and membranes.
Abstract: Received 18 July 2011; accepted 25 November 2011DOI 10.1002/app.36611Published online 20 March 2012 in Wiley Online Library (wileyonlinelibrary.com).ABSTRACT: Electrospun nanofibrous webs are impor-tant in nanotechnology applications due to their high sur-face area and interconnected porosity. In this study, theeffect of electrospinning duration on some physical andmechanical properties of polyurethane (PU) electrospunwebs is investigated for potential applications such as pro-tective clothing and membranes. The results show that thethickness and weight of webs and subsequently their ten-sile strength increase linearly with the electrospinning du-ration. Air permeability of nanofibrous webs decrease andhydrostatic pressure increases nonlinearly while watervapor permeability remains constant. This work showsthat air permeability of PU webs follows Fick’s law of dif-fusion. Some regression models have been proposed todescribe electrospun membranes behavior. The results ofthis investigation indicate that this new generation ofnanofibrous materials has a good potential for applicationas membrane in protective clothing.
TL;DR: In this article, a branch exchange method of single loop is proposed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems, and a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction.
Abstract: Network reconfiguration and capacitor placement have been widely employed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems. Reconfiguration method proposed in this paper is based on a simple branch exchange method of single loop. In this simple method of branch exchange, loops selection sequence affects the optimal configuration and the network loss. Therefore, this method has been improved by optimizing the sequence of loops selection for minimizing the energy losses in this paper. Also, a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction. For more practical application of the proposed method, different load patterns are considered and a fast method of total energy loss calculation is employed for the economic optimization of energy losses during the planning horizon. Discrete genetic algorithm (GA) is used to optimize the location and size of capacitors and the sequence of loops selection. In fact, the capacitor sizes have been considered as discrete variables. Simulated annealing (SA) is also applied to compare the performance of convergence. The proposed algorithm is effectively tested on a real life 77-bus distribution system with four different kinds of load patterns.
TL;DR: In this article, a power management strategy (PMS) optimization is integrated with the sizing procedure of the hybrid system to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES).
Abstract: The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.
TL;DR: In this paper, the authors report evolving pore formation in both surface and interior structures of polystyrene (PS) fibers electrospun from solutions of dimethylformamide (DMF), as low, and tetrahydrofuran (THF) as high volatile solvents.
TL;DR: In this article, the operational matrix of fractional derivative of order α in the Caputo sense using the linear B-spline functions is constructed, which reduces such problems to those of solving a system of algebraic equations.
TL;DR: It is concluded that the changes in left-hemisphere brain's structure of ADHD from that of the non-ADHD are so much that L and C can distinguish the ADHD brain from the non -ADHD brain in the delta EEG sub-band.
Abstract: This article presents a new methodology for investigation of the organization of the overall and hemispheric brain network of patients with attention-deficit hyperactivity disorder (ADHD) using theoretical analysis of a weighted graph with the goal of discovering how the brain topology is affected in such patients. The synchronization measure used is the nonlinear fuzzy synchronization likelihood (FSL) developed by the authors recently. Recent evidence indicates a normal neocortex has a small-world (SW) network with a balance between local structure and global structure characteristics. Such a network results in optimal balance between segregation and integration which is essential for high synchronizabilty and fast information transmission in a complex network. The SW network is characterized by the coexistence of dense clustering of connections (C) and short path lengths (L) among the network units. The results of investigation of C show the local structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is recognizable in the delta electroencephalograph (EEG) sub-band. Also, the results of investigation for L show the global structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is observable in the delta EEG sub-band. It is concluded that the changes in left-hemisphere brain's structure of ADHD from that of the non-ADHD are so much that L and C can distinguish the ADHD brain from the non-ADHD brain in the delta EEG sub-band.
TL;DR: A review of the literature on cross-linked cotton fabrics can be found in this paper, where the formaldehyde and non-formaldehyde based cross-link agents, applications of enzyme and nanotechnology, new approaches and future aspects of cotton cross-linking have been thoroughly discussed.