Visualization of dynamic fiber-matrix interfacial shear debonding

To visualize the debonding event in real time for the study of dynamic crack initiation and propagation at the fiber–matrix interface, a modified tension Kolsky bar was integrated with a high-speed synchrotron X-ray phase-contrast imaging setup. In the gage section, the pull-out configuration was utilized to understand the behavior of interfacial debonding between SC-15 epoxy matrix and S-2 glass fiber, tungsten wire, steel wire, and carbon fiber composite Z-pin at pull-out velocities of 2.5 and 5.0 m s^?1. The load history and images of the debonding progression were simultaneously recorded. Both S-2 glass fiber and Z-pin experienced catastrophic interfacial debonding whereas tungsten and steel wire experienced both catastrophic debonding and stick–slip behavior. Even though S-2 glass fiber and Z-pin samples exhibited a slight increase and tungsten and steel wire samples exhibited a slight decrease in average peak force and average interfacial shear stress as the pull-out velocities were increased, no statistical difference was found for most properties when the velocity was increased. Furthermore, the debonding behavior for each fiber material is similar with increasing pull-out velocity. Thus, the debonding mechanism, peak force, and interfacial shear stress were rate insensitive as the pull-out velocity doubled from 2.5 to 5.0 m s^?1. Scanning electron microscope imaging of recovered epoxy beads revealed a snap-back behavior around the meniscus region of the bead for S-2 glass, tungsten, and steel fiber materials at 5.0 m s^?1 whereas those at 2.5 m s^?1 exhibited no snap-back behavior.     

Optimal Implementation of Photovoltaic and Battery Energy Storage in Distribution Networks

Recently, implementation of Battery Energy Storage (BES) with photovoltaic (PV) array in distribution networks is becoming very popular in overall the world. Integrating PV alone in distribution networks generates variable output power during 24-hours as it depends on variable natural source. PV can be able to generate constant output power during 24-hours by installing BES with it. Therefore, this paper presents a new application of a recent metaheuristic algorithm, called Slime Mould Algorithm (SMA), to determine the best size, and location of photovoltaic alone or with battery energy storage in the radial distribution system (RDS). This algorithm is modeled from the behavior of SMA in nature. During the optimization process, the total active power loss during 24-hours is used as an objective function considering the equality and inequality constraints. In addition, the presented function is based on the probabilistic for PV output and different types of system load. The candidate buses for integrating PV and BES in the distribution network are determined by the real power loss sensitivity factor (PLSF). IEEE 69-bus RDS with different types of loads is used as a test system. The effectiveness of SMA is validated by comparing its results with those obtained by other well-known optimization algorithms.     

Structural,dielectric and electrical properties of Sol–gel auto-combustion technic of CuFeCr0.5Ni0.5O4 ferrite

Journal of Materials Science - The CuFeCr0.5Ni0.5O4 (CFO) compound was synthesized using sol–gel reaction combustion technic. The structural analysis showed that the obtained composites have...     

Image and video denoising by combining unsupervised bounded generalized gaussian mixture modeling and spatial information

Multimedia Tools and Applications - In recent years, a great deal of effort has been expended on developing robust solutions for images quality degradation caused mainly by noise. In this paper, we...     

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.     

A multi-microcarrier of metronidazole-biopolymers complexes as a potential vaginal delivery system

The advantages of multiparticulate carriers over monolithic one are well known. In this study, mucoadhesive micropellets (MPs) composed of metronidazole (MTZ)–polysaccharide(s) polyelectrolytes complexes were prepared to be used as a localized vaginal healthcare product. The prepared all-natural MPs were characterized using FTIR spectroscopy as well as scanning electron microscopy studies. The MPs were evaluated by determination of drug encapsulation efficiency (EE), particle size (PS), drug release parameters, and ex vivo bioadhesivity using vaginal mucosa. MP-D composed of (MTZ:alginate:polycarbophil?=?1:0.5:0.5) attained the highest EE (97.67%) as well as the most extended drug release properties. Microbiological study comparing MP-D to the market product (Amrizole vaginal suppository) showed the superiority of MP-D by its capability to constantly inhibit fungal growth all-over 24?h, while Amrizole suppository was effective for only 8?h.     

New formulation of GNSS acquisition with CFAR detection

This paper deals with the analysis of the acquisition process performed by a global navigation satellite system (GNSS) receiver with a pilot and data channel or in case of GNSS hybrid receiver. Signal acquisition decides the presence or absence of GNSS signal by comparing signal under test with a fixed threshold and provides a code delay and a Doppler frequency estimation, but in low signal conditions or in a noisy environment; acquisition systems are vulnerable and can give a high false alarm and low detection probability. Firstly, we introduce a cell‐averaging‐constant false alarm rate (CFAR) then a data‐pilot cell‐averaging‐CFAR detector fusion based to deal with these situations. In this context, we use a new mathematical derivation to develop a closed‐form analytic expressions for the probabilities of detection and false alarm. The performances of the proposed detector are evaluated and compared with a non‐CFAR case through an analytical and numerical results validated by Mont Carlo simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

Integrated ion exchange mixed bed with reverse osmosis and nanofiltration for isolation of neutral dissolved organic matter from natural waters

The aim of this study was to isolate the neutral dissolved organic matter (NDOM) and the low molecular weight neutrals (LMWN) from natural waters. The coupling of an ion exchange mixed bed (IEXMB) with reverse osmosis (RO) and nanofiltration was the main hypothesis. IEXMB removed charged species, while the neutral molecules were isolated in the demineralised water and then concentrated by RO without any osmotic pressure or fouling limits. Neutrals isolation and unlimited concentration, gives this paper its originality. The nanofiltration (NF) step allows for the isolation of the LMWN. The studied reservoir water NDOM and LMWN represented respectively 35% of the dissolved organic matter (DOM) and 34% of the NDOM. Aromatic compounds were found in both fractions. The UV254 absorbance measured before and after the IEXMB evidenced the water quality ‘signature’. IEX has never been studied as fractionation method of DOM. This IEXMB approach is thus quite novel.     

A hybrid classifier fusion approach for motor unit potential classification during EMG signal decomposition

In this paper, we propose a hybrid classifier fusion scheme for motor unit potential classification during electromyographic (EMG) signal decomposition. The scheme uses an aggregator module consisting of two stages of classifier fusion: the first at the abstract level using class labels and the second at the measurement level using confidence values. Performance of the developed system was evaluated using one set of real signals and two sets of simulated signals and was compared with the performance of the constituent base classifiers and the performance of a one-stage classifier fusion approach. Across the EMG signal data sets used and relative to the performance of base classifiers, the hybrid approach had better average classification performance overall. For the set of simulated signals of varying intensity, the hybrid classifier fusion system had on average an improved correct classification rate (CCr) (6.1%) and reduced error rate (Er) (0.4%). For the set of simulated signals of varying amounts of shape and/or firing pattern variability, the hybrid classifier fusion system had on average an improved CCr (6.2%) and reduced Er (0.9%). For real signals, the hybrid classifier fusion system had on average an improved CCr (7.5%) and reduced Er (1.7%).     

Lignocellulosic polymer composite IV

Palm leaves as a woody lignocellulose, together with polystyrene, were used to produce composites. Chemithermal mechanical pulps (CTMP) were obtained from palm leaves under alkaline or acidic conditions. Appropriate bending strength was obtained from palm leaves and their CTMP pulps prepared under neutral or acidic conditions. The bulky fibers resulted from the alkaline pulps lead to composites of low bending strength. Thus, the cooking conditions of the palm leaves to obtain CTMP pulp play an important role on the properties of the composites. The nonbulky fibers lead to the formation of trapped pockets air as the number of the hydrogen bond are few. The presence of these air pockets allows the polystyrene solution to enter forming bonding between the interfaces. It is also found that the lower the density of the composites, the lower the internal bond strengths. The chemical constituents of the CTMP pulps, as well as the yields of the pulps, may influence the properties of the composites. Increasing the percentage of polystyrene in the composites, the mechanical properties increased. The water uptake and the swellability decreased until 20% polystyrene concentration and then levelled off. The thickness and density behaved the same. However, the type of substrate of the composite and the weight fraction are the important factors in determining the properties of the composites. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 69: 845–855, 1998