Multi-Agent Framework for Spatial Load Forecasting

A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.

Anomalous metamagnetic-like transition in a FeRh/Fe3Pt interface occurring at T approximate to 120 K in the field-cooled-cooling curves for low magnetic fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariated variance analysis applied to biological experiments: An analysis with curves of rats teeth growth as influenced by colchicine

The evaluation of the growth of incisor teeth of rats as influenced by colchicine (doses of 25, 50, 100 and 200 μg/kg) injected during 10 and 18 days is performed using a multivariated variance analysis, which allowed a global view of the results, showing that: there are differences in the growth of teeth of control group (untreated rats) and those treated with colchicine, in the measurements made at the 4th, 7th and 10th days of experiment); there is no difference in the growth of the teeth between the groups treated during 10 and 18 days, except in the measurements made at the 7th day; there is no influence of the doses of colchicine in the group treated during 10 days and in the group treated during 18 days - only at the 7th day is observed an influence of the doses used; and there was no significant interaction between treatment and days of measurement, showing the similarity of the groups during the experiment.

On the geometry of non-classical curves

In this paper we relate the numerical invariants attached to a projective curve, called the order sequence of the curve, to the geometry of the varieties of tangent linear spaces to the curve and to the Gauss maps of the curve. © 1992 Sociedade Brasileira de Matemática.

Growth curves for Macrobrachium rosenbergii in semi-intensive culture in Brazil

Four 0.02-ha earthen ponds at the UNESP Aquaculture Center, Jaboticabal, São Paulo, Brazil, were stocked with newly metamorphosed Macrobrachium rosenbergii post-larvae at 1.5 animals/m2. After 8 mo, prawn density at harvest ranged from 0.3/ m2 to 0.8/m2. Growth curves were determined for each population using von Bertalanffy growth functions. Asymptotic maximum length and asymptotic maximum weight increased as final population size decreased indicating that a strong density effect on prawn growth occurs in semi-intensive culture, even when populational density varies within a small range of less than 1 animal/m2.

Synchronous machines parameters identification using load rejection test data

This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. The quadrature axis parameters are obtained with a rejection under an arbitrary reference, reducing the present difficulties.

Analytical functions for the calculation of hyperspherical potential curves of atomic systems

We present angular basis functions for the Schrödinger equation of two-electron systems in hyperspherical coordinates. By using the hyperspherical adiabatic approach, the wave functions of two-electron systems are expanded in analytical functions, which generalizes the Jacobi polynomials. We show that these functions, obtained by selecting the diagonal terms of the angular equation, allow efficient diagonalization of the Hamiltonian for all values of the hyperspherical radius. The method is applied to the determination of the 1S e energy levels of the Li + and we show that the precision can be improved in a systematic and controllable way. ©2000 The American Physical Society.

A fast electric load forecasting using neural networks

The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.

Duality of osculating developables of projective curves

We give a description of the dual varieties of all developables of osculating linear spaces to a projective curve in terms of the higher order dual varieties of the curve, in arbitrary characteristic. We also determine for these varieties the inseparable degrees of the projections from the conormal varieties onto their dual varieties.

Identification of synchronous machine parameters using load rejection test data

This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. By machine modeling one can obtain the quadrature parameters through a load rejection under an arbitrary reference, reducing the present difficulties. The proposed method is applied to a real machine.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

A load cell for grain-propelled ballistic rocket thrust measurement

A 1000-kgf resistive strain-gauge load cell has been developed for quality testing of rocket propellant grain. A 7075-T6 aluminum alloy has been used for the elastic column, in which 8 uniaxial, 120-Ω strain gauges have been bonded and connected to form a full Wheatstone bridge to detect the strain. The chosen geometry makes the transducer insensitive to moments and, also, to the temperature. Experimental tests using a universal testing machine to imposed compression force to the load cell have demonstrated that its behavior is linear, with sensitivity of 2.90 μV/kgf ± 0.34%, and negligible hysteresis. The designed force transducer response to a dynamic test has been comparable to that of a commercial load cell. © 2005 IEEE.

Method for estimating railroad track settlements due to dynamic traffic loads

This paper is the result of real-scale physical modeling study designed to simulate the load-deformation characteristics of railroad foundation systems that include the railroad ties, the ballast, and the sub-base layers of a railroad embankment. The study presents comparisons of the application of dynamic loads of 100kN on the rails, and the resulting deformations during a 500,000 cycle testing period for three rail support systems; wood, concrete and steel. The results show that the deformation curve has an exponential shape, with the larger portion of the deformation occurring during the first 50,000 load cycles followed by a tendency to stabilize between 100,000 to 500,000 cycles. These results indicate that the critical phase of deformations of a new railroad is within the first 50,000 cycles of loading, and after that, it slowly attenuates as it approaches a stable value. The paper also presents empirically derived formulations for the estimation of the deformations of the rail supports as a result of rail traffic.

Characteristics of the double-torsion test to determine the R-curve of ceramic materials

Double-torsion tests were carried out on a commercial ceramic floor tile to verify whether this test is suitable for determining the R-curve of ceramics. The instantaneous crack length was obtained by means of compliance calibration, and it was found that the experimental compliance underestimates the real crack length. The load vs. displacement curves were also found to drop after maximum loading, causing the stress intensity factor to decline. The R-curves were calculated by two methods: linear elastic fracture mechanics and the energetic method. It was obtained that the average values of crack resistance, R, and the double of the work of fracture, 2 · γwof, did not depend on notch length, a0, which is a highly relevant finding, indicating that these parameters were less dependent on the test specimen's geometry. The proposal was to use small notches, which produce long stable crack propagation paths that in turn are particularly important in the case of coarse microstructures.