Pairing effect and tensile properties of laminated high-performance hybrid composites prepared using carbon/glass and carbon/aramid fibers

Many attempts have been made to fabricate lightweight, high-performance, and low-cost polymeric composites. To improve the mechanical performance of the same material compared to conventional composites, paired hybrid materials were manufactured with different lamination structures. Each of six types of hybrid composite was designed by lamination pairing of carbon/aramid fabric and carbon/glass fabric using VARTM. The dependence of the mechanical properties of the samples on the pairing effects of the lamination structures was investigated. All pairing materials did not lead to a large increase of tensile strength due to the domination of carbon fiber, but the mechanical properties of specific laminates were clearly changed by the particular pairing sequence used. Using the limited material, the design of an effective structure was the central laminating condition with a good tensile and bending properties. Laminating position of the carbon fiber was found to play an important role in the stacking design of hybrid composites.     

Homogenization with uncertainty in Poisson ratio for polymers with rubber particles

The main aim of this work is dual computer analysis of probabilistic coefficients for the homogenized tensor of the polymer filled with the rubber particles having randomized Poisson ratios of both constituents. The major issue is to verify an influence of a randomness in rubber Poisson ratio close to the compressibility limit on the uncertainty of the effective tensor probabilistic characteristics. Probabilistic analysis presented here is carried out using mainly the stochastic perturbation technique provided by the common application of the traditional FEM commercial code ABAQUS and the symbolic computations package MAPLE. This FEM-based technique employs polynomial response function of the optimum order recovered from the weighted least squares method and following a set of deterministic solutions obtained for various values of the randomized input parameter. Optimization procedure is released entirely into a symbolic environment, where maximization of the correlation factor together with minimization of the fitting variance and approximation error are applied. Homogenization technique consists in equating of deformation energies for the real composite and the artificial one characterized by the effective elasticity tensor with uncertainty.     

Dynamic mechanical analysis and thermal properties of LLDPE/EVA/modified silica nanocomposites

The effect of hexamethylene disilazane modified nanosilica on the dynamic mechanical analysis (DMA), crystallization, melting and thermal degradation behavior of linear low density polyethylene/ethylene vinyl acetate copolymer (LLDPE/EVA) blends are explored.Detailed DMA analysis is carried out in order to investigate the reinforcing behavior of nanosilica adopting Kerner–Nielson model. Oxidative degradation and thermal stabilities of samples are also studied by the thermogravimetery analysis. The high content of nanosilica particles results in significant shift of degradation temperature to higher temperatures in the oxygen atmosphere. This behavior might be attributed to the barrier properties of nanoparticles against oxygen and gaseous degradation products. However, incorporation of modified nanosilica into LLDPE/EVA blend is decreased the onset of degradation temperature of the unfilled system. In nitrogen atmosphere, no changes are observed in the thermal degradation range and only a reduction is documented in the onset of degradation temperature. Considering important role of onset of degradation temperature, activation energy of starting of degradation temperature is calculated utilizing Kissinger-Ozawa model in both oxygen and nitrogen atmospheres. Results showed that activation energy of degradation reaction is decreased by ∼ 20 kJ/mol. This decrease is owing to the release of modifiers from the nanoparticles.     

Prism coupling method to evaluate the light extraction efficiency of outcoupling substrates

One of the key challenges in organic light-emitting diodes (OLEDs) for lighting applications is efficient light extraction from the planar, multi-layered OLED stack. Several different light extraction approaches are being explored currently by researchers, however characterizing light extraction films after fabricating OLEDs is not a viable approach when the outcoupling films have large surface roughness and is time consuming as well. Here we apply prism coupling method (PCM), a simple and elegant tool, to characterize outcoupling films. We show the effectiveness of PCM in estimating light extraction efficiency of outcoupling films. PCM can expedite selection and optimization of various light extraction approaches without the need to build OLEDs. The experimental results are corroborated by the optical simulations done using ray tracing method taking into account Mie scattering from wavelength sized spherical inclusions in an outcoupling film.     

The effect of ethylene glycol/citric acid molar ratio in the initial precursor of TiO2 nanoparticle paste synthesized by a polymerizable complex method on the photovoltaic properties of dye-sensitized solar cells

A polymerizable complex method, also known as a Pechini method, was employed to synthesize titanium-sol (Ti-sol) as a matrix for TiO₂ nanoparticle paste, suitable for fabrication of semiconducting mesoporous TiO₂ layer as a photoanode of dye-sensitized solar cells (DSSCs). The purpose of the present work was to investigate the effect of ethylene glycol (EG)/citric acid (CA) molar ratio (Z), in the initial Ti-sol precursor, on the photovoltaic properties of DSSCs. From viscosity (µ) measurement and Fourier transform infrared (FTIR) spectrum of Ti-sols it was revealed that the amount of polyester in the sol decreases with increasing Z. The higher polyester content in the Ti-sols with lower Z ratios led to their higher surface tension (γ) and as a result the higher contact angle (α). The low wettability of fluorine doped tin oxide (FTO) coated glass with Ti-sol was the main reason of micro-cracking of TiO₂ layers after sintering. This effect was significant for lower Z ratios. Micro-cracks increase the back electron–hole recombination rate. Also, at higher Z ratio, the back electron–hole recombination rate increased, which was due to the lower Ti⁴⁺ ions in the Ti-sol precursor and poor interconnection between TiO₂ nanoparticles. Therefore, the maximum short circuit current density (I_sc) and the maximum conversion efficiency (η) were obtained for Z=4. Fill factor (FF) decreased with increasing Z. But, open circuit voltage (V_oc) was nearly independent of Z.     

Low‐Temperature Chemical Synthesis of High‐Purity Diacylglycerols (DAG) from Monoacylglycerols (MAG)

A chemical method was developed for low‐temperature synthesis of DAG from MAG followed by an easy purification procedure in order to obtain high‐purity DAG. Solvent‐assisted and solvent‐free reaction conditions were used, combined with different catalysts (sodium methoxide, p‐toluenesulfonic acid, methanesulfonic acid, and sulfuric acid). All reactions were performed at 35 and 70 °C. By increasing both acidity and polarity of the catalyst the equilibrium shifts towards the formation of DAG. When using sulfuric acid in solvent‐assisted condition at 70 °C, 88 % conversion was obtained after 20 min of reaction (77 % w/w DAG in the reaction mixture after evaporation of the solvent). After purifying by means of column chromatography, 96 % pure DAG were obtained. The overall yield of DAG was 81 %.     

综放高瓦斯矿井煤层瓦斯涌出量综合预测

为了成功预测竹林山煤矿综放高瓦斯矿井大采高工作面煤层瓦斯涌出量,以主采3号煤层为主要研究对象,针对3号煤层以往开采情况,通过布设测点测量其煤层瓦斯含量和了解相邻矿井瓦斯含量,采用分源预测法、回归法及统计法等预测方法得到了3号煤层瓦斯含量的分布规律,并绘制了3号煤层的瓦斯含量等值线图。对矿井不同生产时期的瓦斯含量进行预测,得到了生产前期、中期及后期采区的最大绝对瓦斯涌出量和最大相对瓦斯涌出量,说明了竹林山煤矿各个时期均属于高瓦斯矿井。     

Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection

In a deregulated multi-area electrical power system the objective is to determine the most economical generation dispatch strategy that could satisfy the area load demands, the tie-line limits and other operating constraints. Usually, economic dispatch (ED) deals only with the cost minimization, but minimization of emission content has also become an equally important concern due to the mandatory requirement of pollution reduction for environmental protection. Environmental economic dispatch (EED) is a complex multi-objective optimization (MOO) problem with conflicting goals. Normally a fuzzy ranking is employed to rank the large number of Pareto solutions obtained after solving a MOO problem. But in this paper the preference of the decision maker (DM) is used to guide the search and to select the population for the next generation. An improved differential evolution (DE) method is proposed where the selection operation is modified to reduce the complexity of multi-attribute decision making with the help of a fuzzy framework. Solutions are assigned a fuzzy rank on the basis of their level of satisfaction for different objectives before the population selection and then the fuzzy rank is used to select and pass on better solutions to the next generation. A well distributed Pareto-front is obtained which presents a large number of alternate trade-off solutions for the power system operator. A momentum operation is also included to prevent stagnation and to create Pareto diversity. Studies are carried out on three test cases and results obtained are found to be better than some previous literature.     

Prediction of composite suitability index for physical habitat simulations using the ANFIS method

A physical habitat simulation is a useful tool for assessing the impact of river development or restoration on river ecosystem. Conventional methods of physical habitat simulation use the habitat suitability index models and their success depends largely on how well the model reflects monitoring data. One of preferred habitat suitability index models is habitat suitability curves, which are normally constructed based on monitoring data. However, these curves can easily be affected by the subjective opinion of the expert. This study introduces the ANFIS method for predicting the composite suitability index for use in physical habitat simulations. The ANFIS method is a hybrid type of artificial intelligence technique that combines the artificial neural network and fuzzy logic. The method is known to be a powerful approach especially for developing nonlinear relationships between input and output datasets.In this study, the ANFIS method was used to predict the composite suitability index for the physical habitat simulation of a 2.5 km long reach of the Dal River in Korea. Zacco platypus was chosen as the target fish of the study area. A 2D hydraulic simulation was performed, and the hydraulic model was validated by comparing the measured and predicted water surface elevations. The distribution of the composite suitability index predicted by the ANFIS model was compared with that using the habitat suitability curves. The comparisons reveal that the two distributions are similar for various flows. In addition, the distribution of the composite suitability index of the Dal River is computed by the ANFIS method using monitoring data for the other watersheds, namely the Hongcheon River, the Geum River, and the Chogang Stream. The monitoring data for the Chogang Stream, correlation pattern of which was the most similar to that of the Dal River, yielded the distribution of the composite suitability index, which was very close to that obtained using data for the Dal River. This is also supported by the mean absolute percentage error for the difference in the weighted usable areas.