Silicone insulators of power transmission lines with a variable inorganic load concentration: Electrical and physiochemical analyses

Polymeric insulation is an increasing tendency in projects and maintenance of electrical networks for power distribution and transmission. Electrical power devices (e. g., insulators and surge arresters) developed by using polymeric insulation presents many advantages compared to the prior power components using ceramic insulation, such as: a better performance under high pollution environment; high hydrophobicity; high resistance to mechanical, electrical and chemical stresses. The practice with silicone insulators in polluted environments has shown that the ideal performance is directly related to insulator design and polymer formulation. One of the most common misunderstandings in the design of silicone compounds for insulators is the amount of inorganic load used in their formulation. This paper attempts to clarify how the variation of the inorganic load amount affects physicochemical characteristics of different silicone compounds. The physicochemical evaluation is performed from several measurements, such as: density, hardness, elongation, tensile strength. In addition, the evaluation of the physicochemical structure is carried out using infrared test and scanning electronic microscopy (SEM). The electrical analysis is performed from the electric tracking wheel and erosion test, in agreement with the recommendation of the International Electrotechnical Commission (IEC). (C) 2014 Elsevier Ltd. All rights reserved.

Evolutionary History of the PER3 Variable Number of Tandem Repeats (VNTR): Idiosyncratic Aspect of Primate Molecular Circadian Clock

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of CAN-based distributed control system for variable rate technology in agricultural machinery

The number of electronic devices connected to agricultural machinery is increasing to support new agricultural practices tasks related to the Precision Agriculture such as spatial variability mapping and Variable Rate Technology (VRT). The Distributed Control System (DCS) is a suitable solution for decentralization of the data acquisition system and the Controller Area Network (CAN) is the major trend among the embedded communications protocols for agricultural machinery and vehicles. The application of soil correctives is a typical problem in Brazil. The efficiency of this correction process is highly dependent of the inputs way at soil and the occurrence of errors affects directly the agricultural yield. To handle this problem, this paper presents the development of a CAN-based distributed control system for a VRT system of soil corrective in agricultural machinery. The VRT system is composed by a tractor-implement that applies a desired rate of inputs according to the georeferenced prescription map of the farm field to support PA (Precision Agriculture). The performance evaluation of the CAN-based VRT system was done by experimental tests and analyzing the CAN messages transmitted in the operation of the entire system. The results of the control error according to the necessity of agricultural application allow conclude that the developed VRT system is suitable for the agricultural productions reaching an acceptable response time and application error. The CAN-Based DCS solution applied in the VRT system reduced the complexity of the control system, easing the installation and maintenance. The use of VRT system allowed applying only the required inputs, increasing the efficiency operation and minimizing the environmental impact.

On suppression of chaotic motions of a portal frame structure under non-ideal loading using a magneto-rheological damper

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Six-element circuit for maximum power point tracking in photovoltaic-motor systems with variable-frequency drives

A low-cost circuit was developed for stable and efficient maximum power point (MPP) tracking in autonomous photo voltaic-motor systems with variable-frequency drives (VFDs). The circuit is made of two resistors, two capacitors, and two Zener diodes. Its input is the photovoltaic (PV) array voltage and its output feeds the proportional-integral-derivative (PID) controller usually integrated into, the drive. The steady-state frequency-voltage oscillations induced by the circuit were treated in a simplified mathematical model, which was validated by widely characterizing a PV-powered centrifugal pump. General procedures for circuit and controller tuning were recommended based on model equations. The tracking circuit presented here is widely applicable to PV-motor system with VFDs, offering an. efficient open-access technology of unique simplicity. Copyright (C) 2010 John Wiley & Sons, Ltd.

Synthesis, crystal structure and magnetic properties of the helical oxalate-bridged copper(II) chain {[(CH3)(4)N](2)[Cu(C2O4)(2)] center dot H2O}(n)

The preparation, crystal structure and magnetic properties of a new oxalate-containing copper(II) chain of formula {[(CH3)(4)N](2)]Cu(C2O4)(2)] center dot H2O}(n) (1) [(CH3)(4)N+ = tetramethylammonium cation] are reported. The structure of 1 consists of anionic oxalate-bridged copper(II) chains, tetramethylammoniun cations and crystallization water molecules. Each copper(II) ion in 1 is surrounded by three oxalate ligands, one being bidentate and the other two exhibiting bis-bidenate coordination modes. Although all the tris-chelated copper(H) units from a given chain exhibit the same helicity, adjacent chains have opposite helicities and then an achiral structure results. Variable-temperature magnetic susceptibility measurements of 1 show the occurrence of a weak ferromagnetic interaction through the oxalate bridge [J = +1.14(1)cm(-1), the Hamiltonian being defined as H = -J Sigma nm S-i . S-j]. This value is analyzed and discussed in the light of available magnetostructural data for oxalate-bridged copper(H) complexes with the same out-of-plane exchange pathway. (C) 2012 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Probabilistic patterns of interaction: the effects of link-strength variability on food web structure

Patterns of species interactions affect the dynamics of food webs. An important component of species interactions that is rarely considered with respect to food webs is the strengths of interactions, which may affect both structure and dynamics. In natural systems, these strengths are variable, and can be quantified as probability distributions. We examined how variation in strengths of interactions can be described hierarchically, and how this variation impacts the structure of species interactions in predator-prey networks, both of which are important components of ecological food webs. The stable isotope ratios of predator and prey species may be particularly useful for quantifying this variability, and we show how these data can be used to build probabilistic predator-prey networks. Moreover, the distribution of variation in strengths among interactions can be estimated from a limited number of observations. This distribution informs network structure, especially the key role of dietary specialization, which may be useful for predicting structural properties in systems that are difficult to observe. Finally, using three mammalian predator-prey networks ( two African and one Canadian) quantified from stable isotope data, we show that exclusion of link-strength variability results in biased estimates of nestedness and modularity within food webs, whereas the inclusion of body size constraints only marginally increases the predictive accuracy of the isotope-based network. We find that modularity is the consequence of strong link-strengths in both African systems, while nestedness is not significantly present in any of the three predator-prey networks.

Differences in diversity, structure, and variability between intertidal and subtidal meiofaunal assemblages

[EN] Meiofaunal assemblages from intertidal and shallow subtidal seabeds were studied at two sites (one dominated by volcanic sands and the other by organogenic sands) at Tenerife (Canary Islands, NE Atlantic Ocean) throughout an entire year (May 2000?April 2001). Specifically, we aimed (i) to test for differences in diversity, structure, and stability between intertidal and subtidal meiofaunal assemblages, and (ii) to determine if differences in the meiofaunal assemblage structure may be explained by environmental factors (granulometric composition, availability of organic matter, and carbonate content in sediments). A total of 103,763 meiofaunal individuals were collected, including 203 species from 19 taxonomic groups (Acari, Amphipoda, Cnidaria, Copepoda, Echinodermata, Gastrotricha, Isopoda, Insecta, Kinorrhyncha, Misidacea, Nematoda, Nemertini, Oligochaeta, Ostracoda, Polychaeta, Priapulida, Sipuncula, Tanaidacea, and Turbellaria). Nematodes were the most abundant taxonomic group. Species diversity was higher in the subtidal than in the intertidal zone at both sites, as a result of the larger dominance of a few species in the intertidal zone. The meiofaunal assemblage structure was different between tidal levels at both sites, the intertidal presenting greater temporal variability (multivariate dispersion) in the meiofaunal assemblage structure than the subtidal. Sediment grain size, here quantified by the different granulometric fractions, explained the variability in meiofaunal assemblage structure to a greater extent than the percentage of carbonates, a variable linked to sediment origin. This study revealed differences in diversity, assemblage structure, and variability between intertidal and subtidal meiofauna.

A multilevel converter structure for grid-connected PV plants

A new conversion structure for three-phase grid-connected photovoltaic (PV) generation plants is presented and discussed in this Thesis. The conversion scheme is based on two insulated PV arrays, each one feeding the dc bus of a standard 2-level three-phase voltage source inverter (VSI). Inverters are connected to the grid by a traditional three-phase transformer having open-end windings at inverters side and either star or delta connection at the grid side. The resulting conversion structure is able to perform as a multilevel VSI, equivalent to a 3-level inverter, doubling the power capability of a single VSI with given voltage and current ratings. Different modulation schemes able to generate proper multilevel voltage waveforms have been discussed and compared. They include known algorithms, some their developments, and new original approaches. The goal was to share the grid power with a given ratio between the two VSI within each cycle period of the PWM, being the PWM pattern suitable for the implementation in industrial DSPs. It has been shown that an extension of the modulation methods for standard two-level inverter can provide a elegant solution for dual two-level inverter. An original control method has been introduced to regulate the dc-link voltages of each VSI, according to the voltage reference given by a single MPPT controller. A particular MPPT algorithm has been successfully tested, based on the comparison of the operating points of the two PV arrays. The small deliberately introduced difference between two operating dc voltages leads towards the MPP in a fast and accurate manner. Either simulation or experimental tests, or even both, always accompanied theoretical developments. For the simulation, the Simulink tool of Matlab has been adopted, whereas the experiments have been carried out by a full-scale low-voltage prototype of the whole PV generation system. All the research work was done at the Lab of the Department of Electrical Engineering, University of Bologna.

Structure of the Southern Tyrrhenian subduction system: insights from seismological analysis of anisotropy and attenuation

The Southern Tyrrhenian subduction system shows a complex interaction among asthenospheric flow, subducting slab and overriding plate. To shed light on the deformations and mechanical properties of the slab and surrounding mantle, I investigated seismic anisotropy and attenuation properties through the subduction region. I used both teleseisms and slab earthquakes, analyzing shear-wave splitting on SKS and S phases, respectively. The fast polarization directions φ, and the delay time, δt, were retrieved using the method of Silver and Chan [1991. SKS and S φ reveal a complex anisotropy pattern across the subduction zone. SKS-rays sample primarily the sub-slab region showing rotation of fast directions following the curved shape of the slab and very strong anisotropy. S-rays sample mainly the slab, showing variable φ and a smaller δt. SKS and S splitting reveals a well developed toroidal flow at SW edge of the slab, while at its NE edge the pattern is not very clear. This suggests that the anisotropy is controlled by the slab rollback, responsible for about 100 km slab parallel φ in the sub-slab mantle. The slab is weakly anisotropic, suggesting the asthenosphere as main source of anisotropy. To investigate the physical properties of the slab and surrounding regions, I analyzed the seismic P and S wave attenuation. By inverting high-quality S-waves t* from slab earthquakes, 3D attenuation models down to 300 km were obtained. Attenuation results image the slab as low-attenuation body, but with heterogeneous QS and QP structure showing spot of high attenuation , between 100-200 km depth, which could be due dehydration associated to the slab metamorphism. A low QS anomaly is present in the mantle wedge beneath the Aeolian volcanic arc and could indicate mantle melting and slab dehydration.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

A soft-tetramer model for diblock copolymer melts: structure formation and geometric characterization

The ability of block copolymers to spontaneously self-assemble into a variety of ordered nano-structures not only makes them a scientifically interesting system for the investigation of order-disorder phase transitions, but also offers a wide range of nano-technological applications. The architecture of a diblock is the most simple among the block copolymer systems, hence it is often used as a model system in both experiment and theory. We introduce a new soft-tetramer model for efficient computer simulations of diblock copolymer melts. The instantaneous non-spherical shape of polymer chains in molten state is incorporated by modeling each of the two blocks as two soft spheres. The interactions between the spheres are modeled in a way that the diblock melt tends to microphase separate with decreasing temperature. Using Monte Carlo simulations, we determine the equilibrium structures at variable values of the two relevant control parameters, the diblock composition and the incompatibility of unlike components. The simplicity of the model allows us to scan the control parameter space in a completeness that has not been reached in previous molecular simulations.The resulting phase diagram shows clear similarities with the phase diagram found in experiments. Moreover, we show that structural details of block copolymer chains can be reproduced by our simple model.We develop a novel method for the identification of the observed diblock copolymer mesophases that formalizes the usual approach of direct visual observation,using the characteristic geometry of the structures. A cluster analysis algorithm is used to determine clusters of each component of the diblock, and the number and shape of the clusters can be used to determine the mesophase.We also employ methods from integral geometry for the identification of mesophases and compare their usefulness to the cluster analysis approach.To probe the properties of our model in confinement, we perform molecular dynamics simulations of atomistic polyethylene melts confined between graphite surfaces. The results from these simulations are used as an input for an iterative coarse-graining procedure that yields a surface interaction potential for the soft-tetramer model. Using the interaction potential derived in that way, we perform an initial study on the behavior of the soft-tetramer model in confinement. Comparing with experimental studies, we find that our model can reflect basic features of confined diblock copolymer melts.

Robust Nonlinear Output Regulation by Identification Tools

The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

Processing-structure-property relationships in solid-state shear pulverization: Parametric study of specific energy

Solid-state shear pulverization (SSSP) is a unique processing technique for mechanochemical modification of polymers, compatibilization of polymer blends, and exfoliation and dispersion of fillers in polymer nanocomposites. A systematic parametric study of the SSSP technique is conducted to elucidate the detailed mechanism of the process and establish the basis for a range of current and future operation scenarios. Using neat, single component polypropylene (PP) as the model material, we varied machine type, screw design, and feed rate to achieve a range of shear and compression applied to the material, which can be quantified through specific energy input (Ep). As a universal processing variable, Ep reflects the level of chain scission occurring in the material, which correlates well to the extent of the physical property changes of the processed PP. Additionally, we compared the operating cost estimates of SSSP and conventional twin screw extrusion to determine the practical viability of SSSP.

Processing-Structure-Property Relationships in Solid-State Shear Pulverization: Parametric Study of specific energy

Solid-state shear pulverization (SSSP) is a unique processing technique for mechanochemical modification of polymers, compatibilization of polymer blends, and exfoliation and dispersion of fillers in polymer nanocomposites. A systematic parametric study of the SSSP technique is conducted to elucidate the detailed mechanism of the process and establish the basis for a range of current and future operation scenarios. Using neat, single component polypropylene (PP) as the model material, we varied machine type, screw design, and feed rate to achieve a range of shear and compression applied to the material, which can be quantified through specific energy input (Ep). As a universal processing variable, Ep reflects the level of chain scission occurring in the material, which correlates well to the extent of the physical property changes of the processed PP. Additionally, we compared the operating cost estimates of SSSP and conventional twin screw extrusion to determine the practical viability of SSSP.