Parameter identification of deep-bar induction motors using genetic algorithm

In recent years, the use of three-phase deep-bar induction motors in power systems has increased. Proper modeling and precise parameter identification of the model are essential for motors’ operating analysis. In this paper, among the proposed models of deep-bar induction motors, a model based on two-axis theory is discussed and developed to improve precision. A real coded genetic algorithm estimates the parameters of the model. The accuracy and validity of the model and its identified parameters are verified with the help of a 5.5 kW, 380 V, 50 Hz, 1,450 rpm deep-bar induction motor.     

A Critical Study of the Compressible Lattice Boltzmann Methods for Riemann Problem

In this paper, the discrete velocity model proposed by Kataoka and Tsutahara (Phys. Rev. E 69(5):056702, 2004) for simulating inviscid flows is employed. Three approaches for improving the stability and the accuracy of this model, especially for high Mach numbers, are suggested and implemented in this research. First, the TVD scheme (Harten in J. Comput. Phys. 49:357?C393, 1983) is used for space discretization of the convective term in the Lattice Boltzmann equation. Next, the modified Lax-Wendroff with artificial viscosity is employed to increase the robustness of the method in supersonic flows. Finally, a combination of TVD and the 2nd order derivative of the distribution function is employed using a differentiable switch. It is found that the recent technique is a more suitable approach for a wide range of Mach numbers. Moreover, the WENO scheme for space discretization has been applied and compared with these newly applied methods.     

Decision fusion of horizontal and vertical trajectories for recognition of online Farsi subwords

Online handwriting is formed by a combination of horizontal and vertical trajectories. If these trajectories are treated separately, new recognition methods are emerged. In contrast, one classifier is often used to recognize handwriting. In this work, some features for x(t) and y(t) signals were proposed and used to make two separate classifiers. After initial recognition by these classifiers, their results were fused for final recognition. Using HMM classifiers and simple product rule for decision fusion, the recognition results of 42 classes of Farsi subwords showed promising achievements.     

A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms

Many research works in mathematical modeling of the facility location problem have been carried out in discrete and continuous optimization area to obtain the optimum number of required facilities along with the relevant allocation processes. This paper proposes a new multi-objective facility-location problem within the batch arrival queuing framework. Three objective functions are considered: (I) minimizing the weighted sum of the waiting and the traveling times, (II) minimizing the maximum idle time pertinent to each facility, and (III) minimizing the total cost associated with the opened facilities. In this way, the best combination of the facilities is determined in the sense of economical, equilibrium, and enhancing service quality viewpoints. As the model is shown strongly NP-hard, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) are proposed to solve the model. Not only new coding is developed in these solution algorithms, but also a random search algorithm is proposed to justify the efficiency of both algorithms. Since the solution-quality of all meta-heuristic algorithms severely depends on their parameters, design of experiments and response surface methodologies have been utilized to calibrate the parameters of both algorithms. Finally, computational results obtained by implementing both algorithms on several problems of different sizes demonstrate the performances of the proposed methodology.     

A survey of shaped-based registration and segmentation techniques for cardiac images

Heart disease is the leading cause of death in the modern world. Cardiac imaging is routinely applied for assessment and diagnosis of cardiac diseases. Computerized image analysis methods are now widely applied to cardiac segmentation and registration in order to extract the anatomy and contractile function of the heart. The vast number of recent papers on this topic point to the need for an up to date survey in order to summarize and classify the published literature. This paper presents a survey of shape modeling applications to cardiac image analysis from MRI, CT, echocardiography, PET, and SPECT and aims to (1) introduce new methodologies in this field, (2) classify major contributions in image-based cardiac modeling, (3) provide a tutorial to beginners to initiate their own studies, and (4) introduce the major challenges of registration and segmentation and provide practical examples. The techniques surveyed include statistical models, deformable models/level sets, biophysical models, and non-rigid registration using basis functions. About 130 journal articles are categorized based on methodology, output, imaging system, modality, and validations. The advantages and disadvantages of the registration and validation techniques are discussed as appropriate in each section.     

Service reliability of offshore wind turbines

A probabilistic formulation is proposed to assess the performance of the support structure of offshore wind turbines based on their probability and expected time of exceeding specified drift thresholds. To this end, novel probabilistic models are developed to predict the mean and standard deviation of the drift ratio response of wind turbine support structures operating under day-to-day loads as a function of the wind turbine geometry and material properties, and loading conditions. The proposed models are assessed using a database of virtual experiments generated using detailed three-dimensional (3D) nonlinear finite element (FE) models of a set of representative wind turbine configurations. The developed models are then used in a random vibration formulation to estimate the probability and expected time of exceeding specified drift thresholds. As an example, the probability and expected time of exceeding specified drift thresholds are estimated for a typical offshore wind turbine at different wind speeds. A comparison is made between the results obtained based on the proposed models, those obtained using simulators commonly used in practice and detailed 3D nonlinear FE analyses.     

A new reactor concept for combining oxidative coupling and steam re‐forming of methane: modeling and analysis

A new and very promising application of auto‐thermal reactors is the coupling of endothermic and exothermic reactions where the product of the endothermic reaction is the desired one. Therefore, in this work, a reactor in which oxidative coupling of methane (OCM) and steam re‐forming of methane (SRM) reactions take place simultaneously was modeled. The results were obtained in a wide range of different conditions such as inlet feed, inlet temperature, portions of OCM and SRM catalysts, and inlet velocity. In selection of the catalysts, more attention was drawn to prevent re‐forming of OCM products. The main parameters of each reaction under different conditions such as conversion of the feed components, products selectivity and yield, temperature in the length of reactor, and component's concentration in the reactor were considered in course of this study. The results revealed that simultaneous OCM and SRM reactions in one reactor will tend to be auto‐thermal, and the waste of energy will be reduced. The results also show that complete conversion of water and majority of methane and oxygen will decrease the amount of unwanted products at the reactor's discharge–a constraint that exists in single reactors of each reaction specially OCM. Copyright © 2011 John Wiley & Sons, Ltd.     

Oxidation of alcohols with tert-butylhydroperoxide catalyzed by Mn (II) complexes immobilized in the pore channels of mesoporous hexagonal molecular sieves (HMS)

The oxidation of alcohols with tert-butylhydroperoxide (TBHP), in the presence of Mn²⁺ complexes immobilized in the pore channels of mesoporous hexagonal molecular sieves (HMS), were investigated. It was found that immobilized [Mn(bpy)₂]²⁺/HMS is an efficient catalyst for the oxidation of alcohols such as benzyl alcohol, n-hexanol and cyclohexanol. The effects of reaction time, amount of Mn²⁺ in the catalyst, type of substrates and oxidants in this catalysis system were investigated. At optimum conditions, TBHP is more efficient oxidant with respect to H₂O₂. Following order has been observed for the percentage of conversions of alcohols: benzylic >1° >2°.     

Putative mechanism for anticancer properties of Ag–PP (NPs) extract

One of the most important challenges in treating cancer is the invasion and the angiogenesis of cancer cells. The synthesis of green nanoparticles (NPs) and their use in therapeutic fields is one of the most effective methods with minimal side effects in cancer treatment. In this study, cytotoxic and anti‐angiogenic effects of silver NPs (AgNPs) coated with palm pollen extract [Ag–PP(NPs)] were evaluated. For this purpose, the cells were treated with NPs and then were subjected to trypan blue testing (48 h). Then, the cancer invasion was evaluated by the scratch procedure and the expressions of the vascular endothelial growth factor (VEGF) and its receptor (VEGF‐R) genes were estimated using real‐time PCR assay. Also, the angiogenesis effect of the NPs was investigated with chick chorioallantoic membrane (CAM) assay. The Ag–PP(NPs) induced cytotoxicity on MCF7 cells. The findings also showed that Ag–PP(NPs) inhibit invasive cancer cells and reduce the expression of VEGF and VEGF‐R and significantly reduced the number and vessels lengths and the lengths and weights of the embryos in CAM assay. Ag–PP(NPs) with the induction of cytotoxic effects, metastatic inhibition and anti‐angiogenesis properties should be considered as an appropriate option for treatment of cancerInspec keywords: nanomedicine, genetics, cellular biophysics, toxicology, patient treatment, silver, cancer, biochemistry, biomedical materials, nanoparticles, nanofabrication, membranesOther keywords: minimal side effects, cancer treatment, silver NPs, cancer invasion, vascular endothelial growth factor, receptor genes, VEGF‐R, real‐time polymerase chain reaction assay, angiogenesis effect, chick chorioallantoic membrane assay, MCF7 cells, invasive cancer cells, cytotoxic effects, putative mechanism, anticancer properties, antiangiogenic effects, antiangiogenesis properties, Ag–PP‐induced cytotoxicity, metastatic inhibition, palm pollen extraction, trypan blue testing, time 48.0 hour, Ag     

Kinetic study of styrene atom transfer radical polymerization from hydroxyl groups of graphene nanoplatelets: Heterogeneities in chains and graft densities

Confinement effect of graphene nanoplatelets on the kinetics of styrene atom transfer radical polymerization was studied by a “grafting from” reaction. Graphene oxide was modified by different amounts of (3‐aminopropyl) triethoxysilane and then alpha‐bromoisobutyryl bromide from the hydroxyl groups. Polymerization of styrene in the presence of modified graphene and free initiator, ethyl alpha‐bromoisobutyrate, was accomplished at 110°C. Then, effect of various graft densities and different graphene loadings on the heterogeneous graft and free polystyrene chains characteristics and also kinetics of polymerization was studied by gas and gel permeation chromatographies. Efficiency of grafting reactions along with the graft contents was studied by X‐ray photoelectron spectroscopy, elemental analysis, and thermogravimetric analysis. Confinement effects of graphene on the relaxation behavior of polystyrene chains and also morphology of the graphenes were studied by differential scanning calorimetry and transmission electron microscopy, respectively. POLYM. ENG. SCI., 55:1720–1732, 2015. © 2014 Society of Plastics Engineers