Instantaneous complex power applied to three-phase machines

The theory presented in this paper was primarily developed to give a physical interpretation for the instantaneous power flow on a three-phase induction machine, without a neutral conductor, on any operational state and may be extended to any three-phase load. It is a vectorial interpretation of the instantaneous reactive power theory presented by Akagi et al. Which, believe the authors, isn't enough developed and its physical meaning not yet completely understood. This vectorial interpretation is based on the instantaneous complex power concept defined by Torrens for single-phase, ac, steady-state circuits, and leads to a better understanding of the power phenomenon, particularly of the distortion power. This concept has been extended by the authors to three-phase systems, through the utilization of the instantaneous space vectors. The results of measurements of instantaneous complex power on a self-excited induction generator's terminals, during an over-load application transient, are presented for illustration. The compensation of reactive power proposed by Akagi is discussed and a new horizon for the theory application is opened.

Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

This paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.

Hybrid methods for lot sizing on parallel machines

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

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Managing Large Data Sets Using Support Vector Machines

Hundreds of Terabytes of CMS (Compact Muon Solenoid) data are being accumulated for storage day by day at the University of Nebraska-Lincoln, which is one of the eight US CMS Tier-2 sites. Managing this data includes retaining useful CMS data sets and clearing storage space for newly arriving data by deleting less useful data sets. This is an important task that is currently being done manually and it requires a large amount of time. The overall objective of this study was to develop a methodology to help identify the data sets to be deleted when there is a requirement for storage space. CMS data is stored using HDFS (Hadoop Distributed File System). HDFS logs give information regarding file access operations. Hadoop MapReduce was used to feed information in these logs to Support Vector Machines (SVMs), a machine learning algorithm applicable to classification and regression which is used in this Thesis to develop a classifier. Time elapsed in data set classification by this method is dependent on the size of the input HDFS log file since the algorithmic complexities of Hadoop MapReduce algorithms here are O(n). The SVM methodology produces a list of data sets for deletion along with their respective sizes. This methodology was also compared with a heuristic called Retention Cost which was calculated using size of the data set and the time since its last access to help decide how useful a data set is. Accuracies of both were compared by calculating the percentage of data sets predicted for deletion which were accessed at a later instance of time. Our methodology using SVMs proved to be more accurate than using the Retention Cost heuristic. This methodology could be used to solve similar problems involving other large data sets.

Stochastic Partial Budgeting: A New Look at an Old Tool

Farm business managers are constantly making adjustments in their businesses for smoother operations and profitability. Many times, these choices involve actions to enhance the financial return of the farm business; while other times these decisions are made out of necessity to minimize the effects of unfavorable conditions or events such as drought or changes in the market conditions. Some of these decisions are relatively simple, requiring making choices among alternatives within an enterprise; while others are complex involving a total overhaul of the business and its enterprises. Alternative choices within an individual enterprise can have a differential impact on farm profitability. Therefore, making the best decision may make the difference between profit or loss for that enterprise. Partial budgeting is very useful in making such changes within an enterprise of a farm.

Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

Elderly Individuals with Diabetes: Adding Cognitive Training to Psychoeducational Intervention

The present research examined the effects of a cognitive training program combined with psychoeducational intervention for diabetic elderly patients. Specifically, it aimed at assessing the effects of an eight-session cognitive training and educational program in diabetic elderly individuals and investigating changes in their awareness about specific aspects of diabetes. The final sample consisted of 34 individuals-19 in the experimental group (EG) and 15 in the control group (CG), all residing in the eastern region of the city of Sao Paulo. The protocol included clinical and sociodemographic questions; the Diabetes Attitudes Questionnaire (ATT-19); Diabetes Knowledge Scale (DKN-A); Mini Mental State Examination (MMSE); Verbal Fluency-animal category (VF); Geriatric Depression Scale (GDS); Short Cognitive Performance Test (SKT); and the Rivermead Behavioral Memory Test (RBMT). Results pointed to a significant difference between the two groups for the ATT-19, DKN, and SKT-memory and SKT-total, and a marginally significant difference for the RBMT history in the posttest. As for the remaining cognitive variables, no changes were observed. Retest effects were not observed in the CG. We concluded that cognitive training combined with psychoeducational intervention in diabetic elderly individuals may be effective in producing cognitive gains as well as attitude and knowledge improvement concerning diabetes mellitus (DM).

An evaluation of dosimetric characteristics of MAGIC gel modified by adding formaldehyde (MAGIC-f)

Purpose: To evaluate the dosimetric characteristics of a new formulation of MAGIC gel, called MAGIC-f, which contains the addition of 3.3% formaldehyde, resulting in a gel with increased thermal stability. Methods: MAGIC-f gel was prepared and stored in hermetically sealed plastic containers. After irradiation, magnetic resonance images (MRI) were acquired to evaluate dose and dose distribution. Dosimetric characterization was performed by means of depth dose measurements, dose response sensitivity and linearity, temporal stability, energy and dose rate dependence, dose integration using sequential beams, temperature influence during MRI acquisition and dose distribution integrity. Results: MAGIC-f depth dose measurements are compatible with the dosimetric table data within +/- 4% uncertainty. The dosimeter's R-2 response varies linearly with dose at least from 0 to 6 Gy. The time-course of the sensitivity of the dosimeter following irradiation, indicated stabilization after 2 weeks. The dosimeter's response to irradiation was altered by 6% when increasing the energy from cobalt beams to 10 MV beams. The dose rate dependence of this new formulation of gel dosimeter is small: less than 2.5% for a variation from 200 to 500 cGy/min, and the dependence with the fractionation scheme is about 50% smaller than for standard MAGIC gel, The dependence on scanning temperature was also verified, and the integrity of the dose distribution was confirmed for a period of 90 days. Conclusions: The results demonstrate the applicability of this new dosimeter in tridimensional dose distribution measurements. (C) 2012 Elsevier Ltd. All rights reserved.

Electromagnetic torque ripple and copper losses reduction in permanent magnet synchronous machines

This paper presents a method for electromagnetic torque ripple and copper losses reduction in (non-sinusoidal or trapezoidal) surface-mount permanent magnet synchronous machines (SM-PMSM). The method is based on an extension of classical dq transformation that makes it possible to write a vectorial model for this kind of machine (with a non-sinusoidal back-EMF waveform). This model is obtained by the application of that transformation in the classical machine per-phase model. That transformation can be applied to machines that have any type of back-EMF waveform, and not only trapezoidal or square-wave back-EMF waveforms. Implementation results are shown for an electrical converter, using the proposed vectorial model, feeding a non-sinusoidal synchronous machine (brushless DC motor). They show that the use of this vectorial mode is a way to achieve improvements in the performance of this kind of machine, considering the electromagnetic torque ripple and copper losses, if compared to a drive system that employs a classical six-step mode as a converter. Copyright (C) 2011 John Wiley & Sons, Ltd.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Period adding cascades: Experiment and modeling in air bubbling

Period adding cascades have been observed experimentally/numerically in the dynamics of neurons and pancreatic cells, lasers, electric circuits, chemical reactions, oceanic internal waves, and also in air bubbling. We show that the period adding cascades appearing in bubbling from a nozzle submerged in a viscous liquid can be reproduced by a simple model, based on some hydrodynamical principles, dealing with the time evolution of two variables, bubble position and pressure of the air chamber, through a system of differential equations with a rule of detachment based on force balance. The model further reduces to an iterating one-dimensional map giving the pressures at the detachments, where time between bubbles come out as an observable of the dynamics. The model has not only good agreement with experimental data, but is also able to predict the influence of the main parameters involved, like the length of the hose connecting the air supplier with the needle, the needle radius and the needle length. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3695345]

EFFECTS OF ADDING LANTHANUM TO Ni/ZrO2 CATALYSTS ON ETHANOL STEAM REFORMING

EFFECTS OF ADDING LANTHANUM TO Ni/ZrO2 CATALYSTS ON ETHANOL STEAM REFORMING. The catalytic performance of Ni/ZrO2 catalysts loaded with different lanthanum content for steam reforming of ethanol was investigated. Catalysts were characterized by BET surface area, X-ray diffraction, UV-vis spectroscopy, temperature programmed reduction, and X-ray absorption fine structure techniques. Results showed that lanthanum addition led to an increase in the degree of reduction of both NiO and nickel surface species interacting; with the support, due to the higher dispersion effect. The best catalytic performance at 450 degrees C was found for the Ni/2LZ catalyst, which exhibited an effluent gaseous mixture with the highest H-2 yield.

Adding value to the Brazilian sisal: acid hydrolysis of its pulp seeking production of sugars and materials

The present work is inserted into the broad context of the upgrading of lignocellulosic fibers. Sisal was chosen in the present study because more than 50% of the world's sisal is cultivated in Brazil, it has a short life cycle and its fiber has a high cellulose content. Specifically, in the present study, the subject addressed was the hydrolysis of the sisal pulp, using sulfuric acid as the catalyst. To assess the influence of parameters such as the concentration of the sulfuric acid and the temperature during this process, the pulp was hydrolyzed with various concentrations of sulfuric acid (30-50%) at 70 A degrees C and with 30% acid (v/v) at various temperatures (60-100 A degrees C). During hydrolysis, aliquots were withdrawn from the reaction media, and the solid (non-hydrolyzed pulp) was separated from the liquid (liquor) by filtering each aliquot. The sugar composition of the liquor was analyzed by HPLC, and the non-hydrolyzed pulps were characterized by viscometry (average molar mass), and X-ray diffraction (crystallinity). The results support the following conclusions: acid hydrolysis using 30% H2SO4 at 100 A degrees C can produce sisal microcrystalline cellulose and the conditions that led to the largest glucose yield and lowest decomposition rate were 50% H2SO4 at 70 A degrees C. In summary, the study of sisal pulp hydrolysis using concentrated acid showed that certain conditions are suitable for high recovery of xylose and good yield of glucose. Moreover, the unreacted cellulose can be targeted for different applications in bio-based materials. A kinetic study based on the glucose yield was performed for all reaction conditions using the kinetic model proposed by Saeman. The results showed that the model adjusted to all 30-35% H2SO4 reactions but not to greater concentrations of sulfuric acid. The present study is part of an ongoing research program, and the results reported here will be used as a comparison against the results obtained when using treated sisal pulp as the starting material.