Preparation of the γ-Al2O3/PANI nanocomposite via enzymatic polymerization

Peroxidase-catalyzed template-guided polymerization of aniline in the presence of γ- alumina nanosheet (NS) particles have been carried out in aqueous media and γ-Al₂O₃/PANI nanocomposite was obtained. The polymerization of aniline occurred in aqueous solution in the presence of SPS (sulfonated polystyrene) as a template and SDS (sodium dodecyl sulfate) as a surfactant. Both obtained nanocomposites were comparable by SEM images. It was demonstrated that the γ-Al₂O₃ NS/PANI-SPS nanocomposite has higher conductivity and the γ-Al₂O₃ NS/PANI-SDS nanocomposite has higher void areas. The higher conductivity of γ-Al₂O₃ NS/PANI-SPS nanocomposite is attributed to the higher coated areas of γ-Al₂O₃ NS during polymerization in comparison with γ-Al₂O₃ NS/PANI-SDS which are not coated efficiently as the former. The FT-IR studies showed that the γ-Al₂O₃ NS/PANI nanocomposite was formed by interaction of the polyaniline (PANI) and γ-Al₂O₃ NS. FTIR also showed that the amount of PANI in γ-Al₂O₃ NS/PANI-SPS is more than in γ-Al₂O₃ NS/PANI-SDS. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers     

Modeling and prioritizing demand response programs in power markets

One of the responsibilities of power market regulator is setting rules for selecting and prioritizing demand response (DR) programs. There are many different alternatives of DR programs for improving load profile characteristics and achieving customers’ satisfaction. Regulator should find the optimal solution which reflects the perspectives of each DR stakeholder. Multi Attribute Decision Making (MADM) is a proper method for handling such optimization problems. In this paper, an extended responsive load economic model is developed. The model is based on price elasticity and customer benefit function. Prioritizing of DR programs can be realized by means of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Considerations of ISO/utility/customer regarding the weighting of attributes are encountered by entropy method. An Analytical Hierarchy Process (AHP) is used for selecting the most effective DR program. Numerical studies are conducted on the load curve of the Iranian power grid in 2007.     

Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source

As a result of today’s rapid socioeconomic growth and environmental concerns, higher service reliability, better power quality, increased energy efficiency and energy independency, exploring alternative energy resources, especially the renewable ones, has become the fields of interest for many modern societies. In this regard, MG (Micro-Grid) which is comprised of various alternative energy sources can serve as a basic tool to reach the desired objectives while distributing electricity more effectively, economically and securely. In this paper an expert multi-objective AMPSO (Adaptive Modified Particle Swarm Optimization algorithm) is presented for optimal operation of a typical MG with RESs (renewable energy sources) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the surplus of energy when it’s needed. The problem is formulated as a nonlinear constraint multi-objective optimization problem to minimize the total operating cost and the net emission simultaneously. To improve the optimization process, a hybrid PSO algorithm based on a CLS (Chaotic Local Search) mechanism and a FSA (Fuzzy Self Adaptive) structure is utilized. The proposed algorithm is tested on a typical MG and its superior performance is compared to those from other evolutionary algorithms such as GA (Genetic Algorithm) and PSO (Particle Swarm Optimization).     

Axial compressive behavior of concrete actively confined by metal strips; part A: experimental study

This paper presents the results of an experimental study on the application of strapping technique for retrofit of concrete compressive specimens. In this technique, standard strapping devices, which are used in the packaging industry, are applied to post-tension high strength metal strips around the concrete columns. Experimental program included axial compressive tests on 72 cylindrical and prismatic compressive specimens, which were actively confined by pre-stressed metal strips. The effects of various parameters on strength and ductility of confined concrete were studied including compressive strength of concrete, mechanical volumetric ratio of confining strips, post-tensioning force in the strip, number of strip layers wrapped around the specimens and details of strip joint. The effects of strength and ductility of confining strips on the behavior of confined specimens were also studied. Longitudinal and lateral strains of concrete and strain of the strips were monitored. Test results showed significant increase in the strength and ductility of specimens due to active confinement by metal strips. It was observed that ductility of confining material plays the most important role in enhancement of concrete ductility. The gain in strength is strongly dependent to the effective mechanical volumetric ratio of confining strips. It was also observed that the active confinement of concrete by post-tensioning the confining element results in stiffer pre-peak response of concrete specimens than the usual passive confinement.     

Adolescents exhibit behavioral differences from adults during instrumental learning and extinction.

Adolescence is associated with the development of brain regions linked to cognition and emotion. Such changes are thought to contribute to the behavioral and neuropsychiatric vulnerabilities of this period. We compared adolescent (Postnatal Days 28–42) and adult (Postnatal Day 60+) rats as they performed a simple instrumental task and extinction. Rats were trained to poke into a hole for a food-pellet reinforcer. After six days of training, rats underwent extinction sessions in which the previously rewarded behavior was no longer reinforced. During extinction, we examined the effects of continued presentation of a cue light and food restriction. Adults and adolescents exhibited similar performance during training, although adolescents made more task-irrelevant pokes, consistent with increased exploration. Adults made more premature pokes, which could indicate a more exclusive focus on the task. During extinction, adolescents made more perseverative (previously reinforced) pokes than adults. This behavior was strongly modulated by the combination of motivational factors present (food restriction and cue light), indicating that adolescents were differentially sensitive to them. Furthermore, food restriction induced greater open-field activity in adolescents but not in adults. Thus, as the neural circuitry of motivated behavior develops substantially during adolescence, so too does the behavioral sensitivity to motivational factors. Understanding how such factors differently affect adolescents may shed light on mechanisms that lead to the development of disorders that are manifested during this period. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

A probabilistic risk-based approach for spinning reserve provision using day-ahead demand response program

Spinning Reserve is one of the ancillary services which is essential to satisfy system security constraints when the power system faces with a contingency. In this paper, Day Ahead Demand Response Program as one of the incentive-based Demand Response programs is implemented as a source of spinning reserve. In this regard, certain number of demands are selected according to a sensitivity analysis, and simulated as virtual generation units. The reserve market is cleared for Spinning Reserve allocation considering a probabilistic technique. A comparison is performed between the absence and existence of Day Ahead Demand Response Program from both economical and reliability viewpoints. Numerical studies based on IEEE 57 bus test system is conducted for evaluation of the proposed method.     

An enhanced microfluidic control system for improving power density of a hydride-based micro fuel cell

Microfuel cells (MFCs) can potentially power emerging technologies that require power sources in the microliter size range. The recent development of a microfluidic mechanism for self-regulated generation of hydrogen has enabled fabrication of MFCs orders of magnitude smaller than previously possible. In this study, we report an order of magnitude enhancement in the power density of a microliter-scale fuel cell incorporating a new microfluidic design. The microfluidic mechanism is part of an on-board hydrogen generator that uses a reaction between a metal hydride, LiAlH₄, and water vapor to generate hydrogen. The hydrogen generated exits the hydride reactor through a porous silicon wall to reach a Nafion-based membrane electrode assembly (MEA). The microfluidic design increased the water vapor release rate to the hydride reactor by one order of magnitude over a previous design. A 9 μL device incorporating the enhanced microfluidic design delivered a power density of 92 W L⁻¹. Details of a parametric study conducted to improve the water vapor release rate of the microfluidic mechanism and performance analysis of the integrated device are presented in this paper.     

Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networks and an adaptive-network-based fuzzy inference system

Various simulation tools were used to develop an effective intelligent system to predict the effects of temperature and pressure on an oil extraction yield. Pomegranate oil was extracted using a supercritical CO₂ (SC-CO₂) process. Several simulation systems including a back-propagation neural network (BPNN), a radial basis function neural network (RBFNN) and an adaptive-network-based fuzzy inference system (ANFIS) were tested and their results were compared to determine the best predictive model. The performance of these networks was evaluated using the coefficient of determination (R²) and the mean square error (MSE). The best correlation between the predicted and the experimental data was achieved using the BPNN method with an R² of 0.9948.