ANN-Based STATCOM Tuning for Performance Enhancement of Combined Wind Farms

Although the wind farms based on squirrel cage induction generators (SCIG) is cheaper than the wind farms based on doubly fed induction generators (DFIG), it is always in desperate need for reactive power compensation. Nevertheless, the wind farms based on DFIG are expensive compared with the SCIG wind farm, it features by its ability to control the active power independent of reactive power. However, combined wind farm (CWF) has been developed to collect the benefits of SCIG and DFIG wind turbines in the same wind farm. In this article, artificial neural network (ANN) is used to evaluate gain parameters of static synchronous compensator (STATCOM) in order to improve the stability performance of CWF. The impact of tuned STATCOM on the performance of CWF during gust wind speed and during three-phase fault is comprehensively investigated. The performance of CWF with STATCOM tuned by ANN is compared with its performance when the STATCOM tuned by the multiobjective genetic algorithm (MOGA) and whale optimization algorithm (WOA). The results show that the performance of CWF can be enhanced using STATCOM tuned by ANN more than MOGA and WOA.     

Analysis matching of 5 GHz operating planar antenna EM characteristics between rigorous raw model,simulation and measurements

Journal of Computational Electronics - One of the challenges in antenna analysis is achieving concordance between the results of a purely theoretical numerical method application and commercial...     

Radiation crosslinking of linear polyethyleneimine-based nanoparticles grafted to poly(glycidyl methacrylate) via trimethylolpropane triacrylate as potential electronic packaging material

Linear polyethyleneimine (L-PEI)-based nanoparticles were synthesized via hydrolysis of poly-2-methyl-2-oxazoline (PMeOx), which was prepared by cationic ring-opening polymerization of the oxazoline five-membered ring. Herein, a kinetic study of the ring-opening polymerization reaction is discussed. The nuclear magnetic resonance spectrum of PMeOx verified the presence of repeating units and terminal groups in the polymer's structure. Molar ratios of PEI and PMeOx were characterized using size exclusion chromatography with low-polydispersity polymer chains as the controlled polymerization reaction. PEI and PMeOx exhibited narrow particle size distribution with hydrodynamic radii of 89 and 67 nm, respectively, as determined via dynamic light scattering analysis. In addition, atomic forces and scanning electron microscopy were used to investigate the topography of the PEI thin films. Poly(glycidyl methacrylate) P(GMA) was grafted onto a PEI chain in the presence of trimethylolpropane triacrylate (TMPTA) as the crosslinking agent to synthesize the P(GMA–PEI–TMPTA) tripolymer via free radical polymerization using gamma irradiation. The thermal characterization of the P(GMA–PEI–TMPTA) tripolymer was conducted using thermogravimetric analysis and differential scanning calorimeter. Generally, the thermal stability of the P(GMA–PEI–TMPTA) tripolymer was improved at low-glycidyl methacrylate concentrations. The prepared tripolymer could be used as effective packaging materials for electronics industries.     

Synthesis,Structure Characterization and Biological Activity of Co (II), Cu (II), and Zn (II) Complexes with (Z)‐3‐((3‐hydroxybenzylidene)amino)pyridin‐1‐ium 4‐(dodecan‐4‐yl)benzenesulfonate Surfactant

(Z)‐3‐((3‐hydroxybenzylidene)amino)pyridin‐1‐ium4‐dodecylbenzenesulfonate anionic surfactant and its cobalt, copper and zinc complexes were synthesized (I, I‐Co, I‐Cu and I‐Zn). The chemical structures of it were characterized by elemental analysis, FTIR, ¹H‐NMR, UV–Vis spectroscopy and atomic adsorption. The effects of the chemical structures of the synthesized anionic surfactant and the type of transition metals on the surface activity are presented in this paper. The thermodynamic parameters show that adsorption and micellization processes are spontaneous. The results of biological activity measurements showed that the synthesized compounds have a great efficiency against gram positive (Bacillus subtilis and Staphylococcus aureus), gram‐ negative bacteria (Pseudomonas aeruginosa and Escherichia coli) and fungi (Candida albicans and Aspergillus niger) as well as the sulfate reducing bacteria (Desulfomonas pigra). The complexation of the anionic surfactant with Co²⁺, Cu²⁺ and Zn²⁺ increase the antimicrobial activity values.     

Synthesis,structure and optical properties of x(CuO)/(1−x)Ni(OH)2 [x=0, 0.1 and 0.3] nanocomposites

The x(CuO)/(1−x)Ni(OH)₂ [x=0, 0.1 and 0.3] nanocomposites were prepared by the hydrothermal method in the presence of the surfactant polyethylenglycol-10000 (PEG-10000). X-ray diffraction (XRD), infrared (IR) spectroscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to characterize the as-prepared samples. The increase of the CuO content led to the increase of the crystallite size of both, the β-Ni(OH)₂ and the CuO. The increase in the crystallite size greatly affects the band gap energy of the as-prepared nanocomposites. The band gap energies of the x(CuO)/(1−x)Ni(OH)₂ nanocomposites were estimated by UV–vis spectroscopic method. UV–vis spectroscopic results showed an apparent decrease in the direct band gap energies. The x(CuO)/(1−x)Ni(OH)₂ [x=0, 0.1 and 0.3] nanocomposites show low band gap energies compared to the Ni(OH)₂ bulk materials. The enhanced optical properties lead to their possible use in photocatalytic and photovoltaic applications.     

Shear Strength of Fiber-Reinforced Sands

Soil reinforcement using discrete randomly distributed fibers has been widely investigated over the last 30 years. Several models were suggested to estimate the improvement brought by fibers to the shear strength of soils. The objectives of this paper are to (1) supplement the data available in the literature on the behavior of fiber-reinforced sands; (2) study the effect of several parameters which are known to affect the shear strength of fiber-reinforced sands; and (3) investigate the effectiveness of current models in predicting the improvement in shear strength of fiber-reinforced sand. An extensive direct shear testing program was implemented using coarse and fine sands tested with three types of fibers. Results indicate the existence of a fiber-grain scale effect which is not catered for in current prediction models. A comparison between measured and predicted shear strengths indicates that the energy dissipation model is effective in predicting the shear strength of fiber-reinforced specimens in reference to the tests conducted in this study. On the other hand, the effectiveness of the predictions of the discrete model is affected by the parameters of the model, which may depend on the test setup and the procedure used for mixing the fibers.     

Effective Level Set Image Segmentation With a Kernel Induced Data Term

This study investigates level set multiphase image segmentation by kernel mapping and piecewise constant modeling of the image data thereof. A kernel function maps implicitly the original data into data of a higher dimension so that the piecewise constant model becomes applicable. This leads to a flexible and effective alternative to complex modeling of the image data. The method uses an active curve objective functional with two terms: an original term which evaluates the deviation of the mapped image data within each segmentation region from the piecewise constant model and a classic length regularization term for smooth region boundaries. Functional minimization is carried out by iterations of two consecutive steps: 1) minimization with respect to the segmentation by curve evolution via Euler-Lagrange descent equations and 2) minimization with respect to the regions parameters via fixed point iterations. Using a common kernel function, this step amounts to a mean shift parameter update. We verified the effectiveness of the method by a quantitative and comparative performance evaluation over a large number of experiments on synthetic images, as well as experiments with a variety of real images such as medical, satellite, and natural images, as well as motion maps.