The legs: a key to bird evolutionary success

Birds are the most diverse and largest group of extant tetrapods. They show marked variability, yet much of this variation is superficial and due to feather and bill color and shape. Under the feathers, the skeleto-muscular system is rather constant throughout the bird group. The adaptation to flight is the explanation for this uniformity. The more obvious morphological adaptations for flight are the wings, but the trunk is always rigid, the tail is short and the neck is flexible, since all these features are correlated with flying behaviour. Unrelated to the exigencies of flight, the legs always have three long bones, and all the birds walk on their toes. This leg structure is a striking plesiomorphic feature that was already present in related dinosaurs. The multi-purpose potential of the legs is the result of the skeletal architecture of a body with three segmented flexed legs. This configuration provides mechanical properties that allow the use of the legs as propulsive, paddling, foraging or grooming tools. It is the association of diverse modes of locomotion-walking, running, hopping, flying and swimming-that have enabled the birds to colonize almost all the environments on Earth.

Optimization of Large-Scale Hydrothermal System Operation

This paper presents the development of a mathematical model to optimize the management and operation of the Brazilian hydrothermal system. The system consists of a large set of individual hydropower plants and a set of aggregated thermal plants. The energy generated in the system is interconnected by a transmission network so it can be transmitted to centers of consumption throughout the country. The optimization model offered is capable of handling different types of constraints, such as interbasin water transfers, water supply for various purposes, and environmental requirements. Its overall objective is to produce energy to meet the country's demand at a minimum cost. Called HIDROTERM, the model integrates a database with basic hydrological and technical information to run the optimization model, and provides an interface to manage the input and output data. The optimization model uses the General Algebraic Modeling System (GAMS) package and can invoke different linear as well as nonlinear programming solvers. The optimization model was applied to the Brazilian hydrothermal system, one of the largest in the world. The system is divided into four subsystems with 127 active hydropower plants. Preliminary results under different scenarios of inflow, demand, and installed capacity demonstrate the efficiency and utility of the model. From this and other case studies in Brazil, the results indicate that the methodology developed is suitable to different applications, such as planning operation, capacity expansion, and operational rule studies, and trade-off analysis among multiple water users. DOI: 10.1061/(ASCE)WR.1943-5452.0000149. (C) 2012 American Society of Civil Engineers.

Tap-Off Power From the Overhead Shield Wires of an HV Transmission Line

In recent years, there was an increase of ancillary service loads, such as signaling systems, inspection robots, surveillance cameras, and other monitoring devices distributed along high-voltage transmission lines which require low-power dc voltage supplies. This paper investigates the use of the induced voltage in the shield wires of an overhead 525 kV transmission line as a primary power source. Since phase current variations throughout the day affect the induced voltage in the overhead ground wire, a step-down dc-dc converter is used after rectification of the ac voltage to provide a regulated dc output voltage. The initial encouraging results obtained indicate that this form of power supply can be a feasible and cost-effective alternative for feeding small ancillary service loads. The simulation results are validated by field measurements as well as the installation of a 200 W voltage stabilization system prototype.

An optimization study of PtSn/C catalysts applied to direct ethanol fuel cell: Effect of the preparation method on the electrocatalytic activity of the catalysts

The aim of this work was to perform a systematic study of the parameters that can influence the composition, morphology, and catalytic activity of PtSn/C nanoparticles and compare two different methods of nanocatalyst preparation, namely microwave-assisted heating (MW) and thermal decomposition of polymeric precursors (DPP). An investigation of the effects of the reducing and stabilizing agents on the catalytic activity and morphology of Pt75Sn25/C catalysts prepared by microwave-assisted heating was undertaken for optimization purposes. The effect of short-chain alcohols such as ethanol, ethylene glycol, and propylene glycol as reducing agents was evaluated, and the use of sodium acetate and citric acid as stabilizing agents for the MW procedure was examined. Catalysts obtained from propylene glycol displayed higher catalytic activity compared with catalysts prepared in ethylene glycol. Introduction of sodium acetate enhanced the catalytic activity, but this beneficial effect was observed until a critical acetate concentration was reached. Optimization of the MW synthesis allowed for the preparation of highly dispersed catalysts with average sizes lying between 2.0 and 5.0 nm. Comparison of the best catalyst prepared by MW with a catalyst of similar composition prepared by the polymeric precursors method showed that the catalytic activity of the material can be improved when a proper condition for catalyst preparation is achieved. (C) 2012 Elsevier B.V. All rights reserved.

Influence of pattern gradation on the design of piezocomposite energy harvesting devices using topology optimization

Piezoelectric materials can be used to convert oscillatory mechanical energy into electrical energy. Energy harvesting devices are designed to capture the ambient energy surrounding the electronics and convert it into usable electrical energy. The design of energy harvesting devices is not obvious, requiring optimization procedures. This paper investigates the influence of pattern gradation using topology optimization on the design of piezocomposite energy harvesting devices based on bending behavior. The objective function consists of maximizing the electric power generated in a load resistor. A projection scheme is employed to compute the element densities from design variables and control the length scale of the material density. Examples of two-dimensional piezocomposite energy harvesting devices are presented and discussed using the proposed method. The numerical results illustrate that pattern gradation constraints help to increase the electric power generated in a load resistor and guides the problem toward a more stable solution. (C) 2012 Elsevier Ltd. All rights reserved.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.