Shiraz, Iran

Shiraz University of Technology is the second public university in the Fars Province in higher technological education, basic and applied research. In 2004, the Government offered technical assistance for establishing an institute of higher education in engineering in Shiraz.Currently the University has about 1100 students, with 3 Bachelor's degree programs and 31 Master's degree & Ph.D. degree programs. Wikipedia.

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Alizadeh M.,Shiraz University of Technology
Journal of Alloys and Compounds | Year: 2011

In this study, aluminum metal matrix composites reinforced with 5 and 10 vol.% B4C particulates were fabricated by repeated roll bonding process. The microstructure of the composites, evaluated by optical microscopy, showed the B4C particles are properly distributed in the aluminum matrix. A combined microstructure strengthening analysis suggested by Sekine and Chen was used to predict the yield strength of the Al/B4C composites. In addition, the yield strength of the composites was determined by tensile tests and compared with the calculated yield strength. The results indicated that there is a good agreement between the calculated yield strength and experimental value. © 2010 Elsevier B.V. All rights reserved.

Nasrifar K.,Shiraz University of Technology
International Journal of Hydrogen Energy | Year: 2010

Eleven equations of state are employed to predict the vapor pressures, liquid and vapor densities, liquid and vapor heat capacities, and vaporization enthalpies and entropies of normal hydrogen along the coexistence curve. The volumetric and thermal properties of gaseous hydrogen together with the speeds of sound, Joule-Thomson coefficients and inversion curves for wide ranges of temperature and pressure are predicted as well. The results are compared with experimental data and the recommended values of standard thermodynamic tables. The best equations of state in predicting the properties of hydrogen (saturated and supercritical) are introduced and reported. © 2010 Professor T. Nejat Veziroglu.

Niknam T.,Shiraz University of Technology
Expert Systems with Applications | Year: 2011

This paper presents an efficient multi-objective honey bee mating optimization (MHBMO) evolutionary algorithm to solve the multi-objective distribution feeder reconfiguration (DFR). The purposes of the DFR problem are to decrease the real power loss, the number of the switching operations and the deviation of the voltage at each node. Conventional algorithms for solving the multi-objective optimization problems convert the multiple objectives into a single objective using a vector of the user-predefined weights. This transformation has several drawbacks. For instance, the final solution of the algorithms extensively depends on the values of the weights. This paper presents a new MHBMO algorithm for the DFR problem. The proposed algorithm utilizes several queens and considers the queens as an external repository to save non-dominated solutions found during the search process. Since the objective functions are not the same, a fuzzy clustering technique is used to control the size of the repository within the limits. The proposed algorithm is tested on two distribution test feeders. © 2010 Elsevier Ltd. All rights reserved.

In recent years, Distributed Generators (DGs) connected to the distribution network have received increasing attention. The connection of enormous DGs into existing distribution network changes the operation of distribution systems. Because of the small X/. R ratio and radial structure of distribution systems, DGs affect the daily Volt/Var control. This paper presents a new algorithm for multiobjective daily Volt/Var control in distribution systems including Distributed Generators (DGs). The objectives are costs of energy generation by DGs and distribution companies, electrical energy losses and the voltage deviations for the next day. A new optimization algorithm based on a Chaotic Improved Honey Bee Mating Optimization (CIHBMO) is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. Since objectives are not the same, a fuzzy system is used to calculate the best solution. The plausibility of the proposed algorithm is demonstrated and its performance is compared with other methods on a 69-bus distribution feeder. Simulation results illustrate that the proposed algorithm has better outperforms the other algorithms. © 2010 Elsevier Ltd.

Shokrollahi H.,Shiraz University of Technology
Materials Science and Engineering C | Year: 2013

This paper is aimed at conducting a survey of the synthetic methods and magnetic properties of nanoparticles as ferrofluids used in biomedicine. As compared with other works in the field, the distinctive feature of the current work is the systematic study of recent advances in ferrofluids utilized in hyperthermia and magnetic resonance imaging (MRI). The most important feature for application of ferrofluids is super-paramagnetic behavior of magnetic cores with relatively high saturation magnetization. Although Fe3O 4 nanoparticles have traditionally been used in medicine; the modified Mn-ferrite has recently received special attention due to its higher saturation magnetization and r2-relaxivity as a contrast agent in MRI. Co-ferrite nanoparticles are also good candidates for hyperthermia treatment because of their high coercivity and magnetocrystalline anisotropy. The thermal decomposition and hydrothermal methods are good candidates for obtaining appropriate super-paramagnetic particles. © 2013 Elsevier B.V.

Shokrollahi H.,Shiraz University of Technology
Materials Science and Engineering C | Year: 2013

Contrast agents are divided into two categories. The first one is paramagnetic compounds, including lanthanides like gadolinium, which mainly reduce the longitudinal (T1) relaxation property and result in a brighter signal. The second class consists of super-paramagnetic magnetic nanoparticles (SPMNPs) such as iron oxides, which have a strong effect on the transversal (T2) relaxation properties. SPMNPs have the potential to be utilized as excellent probes for magnetic resonance imaging (MRI). For instance, clinically benign iron oxide and engineered ferrite nanoparticles provide a good MRI probing capability for clinical applications. Furthermore, the limited magnetic property and inability to escape from the reticuloendothelial system (RES) of the used nanoparticles impede their further advancement. Therefore, it is necessary to develop the engineered magnetic nanoparticle probes for the next-generation molecular MRI. Considering the importance of MRI in diagnosing diseases, this paper presents an overview of recent scientific achievements in the development of newsynthetic SPMNP probes whereby the sensitive and target-specific observation of biological events at the molecular and cellular levels is feasible. © 2013 Elsevier B.V. All rights reserved.

Zarei J.,Shiraz University of Technology
Expert Systems with Applications | Year: 2012

This paper proposes a systematic procedure based on a pattern recognition technique for fault diagnosis of induction motors bearings through the artificial neural networks (ANNs). In this method, the use of time domain features as a proper alternative to frequency features is proposed to improve diagnosis ability. The features are obtained from direct processing of the signal segments using very simple calculation. Three different cases including, healthy, inner race defect and outer race defect are investigated using the proposed algorithm. The ANNs are trained with a subset of the experimental data for known machine conditions. Once the network is trained, efficiency of the proposed method is evaluated using the remaining set of data. The obtained results indicate that using time domain features can be effective in accurate diagnosis of various motor bearing faults with high precision and low computational burden. © 2011 Elsevier Ltd. All rights reserved.

Economic dispatch (ED) plays an important role in power system operation. ED problem is a non-smooth and non-convex problem when valve-point effects of generation units are taken into account. This paper presents an efficient hybrid evolutionary approach for solving the ED problem considering the valve-point effect. The proposed algorithm combines a fuzzy adaptive particle swarm optimization (FAPSO) algorithm with Nelder-Mead (NM) simplex search called FAPSO-NM. In the resulting hybrid algorithm, the NM algorithm is used as a local search algorithm around the global solution found by FAPSO at each iteration. Therefore, the proposed approach improves the performance of the FAPSO algorithm significantly. The algorithm is tested on two typical systems consisting of 13 and 40 thermal units whose incremental fuel cost functions take into account the valve-point loading effects. © 2009 Elsevier Ltd. All rights reserved.

Kavousi-Fard A.,Shiraz University of Technology | Niknam T.,Shiraz University of Technology
Energy | Year: 2014

The main purpose of this paper is to assess the DFR (Distribution Feeder Reconfiguration) strategy as a costless technique to enhance the reliability of the distribution systems. The objective functions to be investigated are: SAIFI (System Average Interruption Frequency Index), AENS (Average Energy Not Supplied), total active power losses and the total network cost. In order to observe the effect of renewable energy sources on the reliability of the power system, wind power source as a popular type of renewable energy source is also considered in the system. In addition, to make the analysis more reliable, the uncertainty of the forecast error of active and reactive loads, wind speed variations as well as the failure rate and repair rate parameters are modeled though the probabilistic load flow. Since the problem investigated is a type of discrete, nonlinear and non-convex optimization problem, a novel self adaptive modified optimization algorithm based on the BA (bat algorithm) is proposed too. The proposed self adaptive modification method makes use of three sub-modifications to give each bat (solution) a choice of preferences during the optimization process. The efficiency and feasibility of the proposed method are studied through a standard IEEE (Institute of Electrical and Electronics Engineers) test system. © 2013 Elsevier Ltd.

Aghaei J.,Shiraz University of Technology | Alizadeh M.-I.,Shiraz University of Technology
Renewable and Sustainable Energy Reviews | Year: 2013

Dealing with Renewable Energy Resources (RERs) requires sophisticated planning and operation scheduling along with state of art technologies. Among many possible ways for handling RERs, Demand Response (DR) is investigated in the current review. Because of every other year modifications in DR definition and classification announced by Federal Energy Regulatory Commission (FERC), the latest DR definition and classification are scrutinized in the present work. Moreover, a complete benefit and cost assessment of DR is added in the paper. Measurement and evolution methods along with the effects of DR in electricity prices are discussed. Next comes DR literature review of the recent papers majorly published after 2008. Eventually, successful DR implementations, around the world, are analyzed. © 2012 Elsevier Ltd. All rights reserved.

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