On the evection resonance and its connection to the stability of outer satellites

In terms of stability around the primary, it is widely known that the semimajor axis of the retrograde satellites is much larger than the corresponding semimajor axis of the prograde satellites. Usually this conclusion is obtained numerically, since precise analytical derivation is far from being easy, especially, in the case of two or more disturbers. Following the seminal idea that what is unstable in the restricted three-body problem is also unstable in the general N-body problem, we present a simplified model which allows us to derive interesting resonant configurations. These configurations are responsible for cumulative perturbations which can give birth to strong instability that may cause the ejection of the satellite. Then we obtain, analytically, approximate bounds of the stability of prograde and retrograde satellites. Although we recover quite well previous results of other authors, we comment very briefly some weakness of these bounds. Copyright (c) 2008 Tadashi Yokoyama et al.

On the stability of the satellites of asteroid 87 Sylvia

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

Study of Stability of Rotational Motion of Spacecraft with Canonical Variables

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mean motion resonances and the stability of a circumbinary disk in a triple stellar system

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Proportional controllers: Direct method for stability analysis and MATLAB implementation

In most cases, the cost of a control system increases based on its complexity. Proportional (P) controller is the simplest and most intuitive structure for the implementation of linear control systems. The difficulty to find the stability range of feedback systems with P controllers, using the Routh-Hurwitz criterion, increases with the order of the plant. For high order plants, the stability range cannot be easily obtained from the investigation of the coefficient signs in the first column of the Routh's array. A direct method for the determination of the stability range is presented. The method is easy to understand, to compute, and to offer the students a better comprehension on this subject. A program in MATLAB language, based on the proposed method, design examples, and class assessments, is provided in order to help the pedagogical issues. The method and the program enable the user to specify a decay rate and also extend to proportional-integral (PI), proportional-derivative (PD), and proportional-integral-derivative (PID) controllers.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Sensitivity analysis for transient stability studies

The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.

Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Stability analysis of power systems described with detailed models by automatic method

The power system stability analysis is approached taking into explicit account the dynamic performance of generators internal voltages and control devices. The proposed method is not a direct method in the usual sense since conclusion for stability or instability is not exclusively based on energy function considerations but it is automatic since the conclusion is achieved without an analyst intervention. The stability test accounts for the nonconservative nature of the system with control devices such as the automatic voltage regulator (AVR) and automatic generation control (AGC) in contrast with the well-known direct methods. An energy function is derived for the system with machines forth-order model, AVR and AGC and it is used to start the analysis procedure and to point out criticalities. The conclusive analysis itself is made by means of a method based on the definition of a region surrounding the equilibrium point where the system net torque is equilibrium restorative. This region is named positive synchronization region (PSR). Since the definition of the PSR boundaries have no dependence on modelling approximation, the PSR test conduces to reliable results. (C) 2008 Elsevier Ltd. All rights reserved.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

Effects of lanthanum modification on dielectric properties of Pb(Zr-0.90,Ti-0.10)O-3 ceramics: enhanced antiferroelectric stability

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

Revegetation on a Removed Topsoil: Effect on Aggregate Stability

The construction of a large reservoir on the Parana River (Selviria, MS, Brazil) disturbed the soil of an extensive agricultural area in which between 5 and 8m of topsoil were removed. In this area, a restoration process was carried out using revegetation with green manure without or with amendments (for 4 years), crops (2 years), and Brachiaria decumbens cultivation for 6 years. The following treatments were used: control plots, T0 (residual subsoil) and T1 (soil tillage without culture); plots with green manure and without amendments: T2 (velvet bean) and T3 (pigeon pea); plots with green manure and with amendments: T4 (limed + velvet bean), T5 (limed + pigeon pea); T6 (limed + gypsum + velvet bean) and T7 (limed + gypsum + pigeon-pea). They were arranged in randomized blocks. After 13 years of rehabilitation process, when the soil was cultivated with brachiaria, the structural stability in three depths was evaluated. Organic-matter content and others chemical properties did not show any relationship with the stability of aggregates of the experimental area as measured by mean weight diameter (MWD). Significant differences between depths were found for MWD and the other parameters measured. Nevertheless, there were no significant differences observed between treatments, independent of the adopted system of revegetation. By taking an absolute value of MWD, the stability of superficial layer was observed in the following sequence: T7 T5 T6 T1 T2 T3 T4 T0. The control plot (T0) gave the lowest value of MWD (1.76mm) in relation to the plots in restoration process. Treatment T7 was the most effective in recovering the stability of aggregates (2.63mm). However, treatments T5 and T6 displayed a similar value. After 13 years of revegetation practices, a slight recovery of the stability was observed, although this is still lower than stability in soils of similar edaphic conditions in the original topsoil of experimental area.

Temporal stability for unpredictable annual climatic variability for Hevea genotype selection

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

Compromised Primary Implant Stability

The aim of this study was to evaluate implants installed with compromised primary stability associated or not with polylactide and polyglycolide copolymer (PLA/PGA). Two 0.4-mm overdrilled defects (3 mm in diameter and 6 mm long) were produced in the right tibia of 25 rabbits. Half of the defects were left untreated, and the other half was filled with PLA/PGA. Implants of 2.6 mm in diameter and 6 mm long were placed into all defects. Animals were killed at 5, 15, 40, and 60 postoperative days, and biomechanical analysis (torque-reverse), histomorphometry, and immunohistochemistry (osteoprotegerin, receptor activator of NFJB ligand [RANKL], osteocalcin, and collagen-1 [ COL- I] staining) were performed. All the implants achieved osseointegration. There were no statistically significant differences in the torque-reverse and in linear contact extension between bone tissue and implant surface and no statistically significant difference in osteoprotegerin, RANKL, osteocalcin, and collagen-1 expression between the studied groups in all studied periods (P > 0.05). We can conclude that osseointegration can occur in compromised primary implant stability situations, and the addition of PLA/PGA did not improve the osseointegration process in this experimental model.