Trajectories in a space with a spherically symmetric dislocation

We consider a new type of defect in the scope of linear elasticity theory, using geometrical methods. This defect is produced by a spherically symmetric dislocation, or ball dislocation. We derive the induced metric as well as the affine connections and curvature tensors. Since the induced metric is discontinuous, one can expect ambiguity coming from these quantities, due to products between delta functions or its derivatives, plaguing a description of ball dislocations based on the Geometric Theory of Defects. However, exactly as in the previous case of cylindric defect, one can obtain some well-defined physical predictions of the induced geometry. In particular, we explore some properties of test particle trajectories around the defect and show that these trajectories are curved but can not be circular orbits.Comment: 11 pages, 3 figure

Model for erosion-deposition patterns

We investigate through computational simulations with a pore network model the formation of patterns caused by erosion-deposition mechanisms. In this model, the geometry of the pore space changes dynamically as a consequence of the coupling between the fluid flow and the movement of particles due to local drag forces. Our results for this irreversible process show that the model is capable to reproduce typical natural patterns caused by well known erosion processes. Moreover, we observe that, within a certain range of porosity values, the grains form clusters that are tilted with respect to the horizontal with a characteristic angle. We compare our results to recent experiments for granular material in flowing water and show that they present a satisfactory agreement.Comment: 8 pages, 12 figures, submitted to Phys. Rev.

Strategic Planning: a model based on Systems Engineering

This work has the main motivation to propose an approach based on Systems Engineering to expand the scope of Organizational Strategic Planning. The proposed method was idealized considering the approaches of Chiavenato & Sapiro (2003) and Loureiro (1999). It is considered that the proposed method was more adequate than the traditional models previously applied

Comparação entre precipitação medida em estações pluviométricas e estimada pelo satélite TRMM.

Na região tropical, a precipitação é reconhecida como uma importante variável climatológica. Entretanto, na Amazônia, boa parte dos estudos se baseia em dados mensais ou anuais, uma vez que dados observacionais diários são escassos. Nesse sentido, este trabalho objetivou realizar uma análise comparativa entre os dados de precipitação estimados pelo sensor Tropical Rainfall Measuring Mission (TRMM) e aqueles obtidos por meio de pluviômetros. A área de estudo abrange a bacia hidrográfica do Rio Ji-Paraná, localizada no leste do Estado de Rondônia. Para os anos compreendidos entre 1998 e 2010 foram utilizados dados de precipitação diária do TRMM, bem como os dados de 52 estações pluviométricas da Agência Nacional de Águas (ANA). Os dados de precipitação foram comparados em períodos diários, decendial e mensal. Os resultados apresentaram coeficiente de determinação de 0,13, 0,49 e 0,73 para comparações realizadas em intervalos diários, decendiais e mensais, respectivamente. Conclui-se que as estimativas do TRMM realizadas com período igual ou superior a 10 dias apresentam maior correlação com os dados observados em superfície

Thermostatistics of overdamped motion of interacting particles

We show through a nonlinear Fokker-Planck formalism, and confirm by molecular dynamics simulations, that the overdamped motion of interacting particles at T=0, where T is the temperature of a thermal bath connected to the system, can be directly associated with Tsallis thermostatistics. For sufficiently high values of T, the distribution of particles becomes Gaussian, so that the classical Boltzmann-Gibbs behavior is recovered. For intermediate temperatures of the thermal bath, the system displays a mixed behavior that follows a novel type of thermostatistics, where the entropy is given by a linear combination of Tsallis and Boltzmann-Gibbs entropies.Comment: 4 pages, 2 figure